Introduction
Background & Rational
Site index
The predicted height at a specific reference age, or site index, is one of the most often used phytocentric indicators of the quality of a forest site (Weiskittel et al., 2011). Since the end of the nineteenth century, the site index has been developed and used extensively (Batho and García, 2006). The relative ease with which site may be determined from field data, its track record of accuracy in volume growth and yield prediction, and the strength of the association between tree height and age in even-aged forests are some of the factors contributing to its widespread acceptance. Site Index (SI) is top height at an index age, usually age 50 in northern forests in Alberta (Monserud et al., 2006). SI is used as an index of productivity and relies on the premise that the height of dominant trees is relatively independent of density and dependent on the inherent productivity of a site or geographic location (Weiskittel et al., 2011). Growth and yield is strongly affected by site quality, and strongly correlated with site index (Weiskittel et al., 2011). However, site index is rarely measured because this would require observation of tree height precisely at age 50. Instead, regression models of height-age relationship for top height trees are commonly used to solve for expected top height at age 50, conditional on current height and age.
Figure 1. Site index for Douglas-fir in western Washington. (Redrawn from King 1966.)
Lodgepole Pine
An important part of Alberta's natural and economic landscapes is lodgepole pine (Pinus contorta var. latifolia Engelm). In terms of ecology, it creates vast forests that serve as homes for a variety of animals, including birds and big mammals like bears and deer (Baah-Acheamfour et al., 2023). The preservation of ecological balance and biodiversity depends on these woods. Lodgepole pine is a vital source of lumber for building, furniture, and paper goods, making it a vital economic component of Alberta's forestry sector (Ghebremichael et al., 2005). Because of its fire adaptation, the species is essential to the health and natural regeneration of forest ecosystems. Lodgepole pine woods are resilient and sustainable because fire helps release seeds from their cones and makes room for future growth (Lotan et al., 1985) . Thus, lodgepole pine is not only a species that is representative of Alberta's forest regions, but it is also essential to the province's economic and environmental health.
Image 1: It shows that lodgepole pine is marketed domestically as part of the single species spruce-pine-fir (SPF) group. SPF lumber is used across North America and Asia for a variety of purposes including structural framing, paneling, shelving, millwork, furniture, doors and trim. (Sources: NorthPac Forestry Group)
How site index is used in forest management?
The most extensively used technique to measure site productivity in woodlands or forests is the site index method. This approach correlates well with timber yields and is simple to apply. Site index is useful in determining an area's potential for planting trees for various uses, even if its primary application is in the appraisal of native forest stands being managed for timber products (Geyer & Lynch, 1987). It assists in choosing the species with the highest potential for productivity at the location for afforestation or reforestation. A high site index denotes a location with favorable growth circumstances, implying that trees planted there will mature rapidly and become sizable, qualifying the site for the production of lumber (Stearns-Smith, 2002). The site index can be used as a management tool to choose species for new planting areas, create management plans, and assess or forecast tree development. The site-index classifications of forest areas are specific in various US forest regions (Geyer & Lynch, 1987). These classes are primarily used for product goals, pruning height decisions, and the allocation of time, labor, and money toward timber stand enhancement activities. The better sites receive the little resources that are available (Geyer & Lynch, 1987). Additionally, the site index plays an important part in the planning of forest operations, such as harvesting and thinning. It gives managers the ability to forecast the trajectory of forest growth, plan harvests for maximum efficiency, and calculate the forest's long-term sustainable output (Bontemps & Bouriaud, 2014). Maintaining the equilibrium between economic goals and the preservation of forest ecosystems depends on this knowledge. The site index is also utilized in forestry investment research and financial planning. The timber volume and growth rate prediction aids in estimating the anticipated returns on investment for forest management initiatives (Bontemps & Bouriaud, 2014). Additionally, it contributes to ecological conservation initiatives by helping to locate and maintain high-value conservation areas that sustain a variety of habitats and animals.
Site index and climate
Global climate models predict that global temperatures will increase by another 3 °C by the end of the twenty-first century (IPCC, 2013). Global climate change has an impact on forest ecosystem dynamics through an overall increase in yearly temperature, an increase in the frequency and intensity of acute climatic events, and modifications to natural disturbance regimes (Iverson et al.2008, Allen et al. 2010, Dai 2013). As a result of climate change, there will be an increase in the frequency of extreme weather events like droughts and heatwaves, which should impact plants with heat and water stress (Grossiord et al., 2020). This stress can lead forest ecosystems to be disrupted (Iverson et al.2008, Allen et al. 2010, Dai 2013). The effects of climate change on forest ecosystems could be dramatic and may alter critical ecosystem goods and services such as wood fiber provision, habitat for biodiversity or carbon storage (Thompson et al., 2009). Climate change may speed up the processes of forest decline and drought stress in water-limited areas, disproportionately affecting the most vulnerable individuals, populations, and species (McDowell et al. 2008; Anderegg et al. 2016). There is considerable evidence that forests contribute to an unusual confluence of critically endangered species, carbon sequestration and storage, water supply, and preservation of human health (Watson et al., 2018).
Image 2: This graph illustrates the change in global surface temperature relative to 1951-1980 average temperatures, with the year 2020 statistically tying with 2016 for hottest on record (Source: NASA's Goddard Institute for Space Studies).
Because of variations in genetics, climate, and the impact of management strategies, the site index for specific stand often varies significantly. Sunlight, precipitation, temperature, wind speed, humidity, and other microclimatic factors can all have an impact on growth, rising temperatures, altered precipitation patterns, and increased frequency of extreme weather events directly impact tree growth rates and health, thus influencing the site index. For instance, higher temperatures and longer growing seasons in some regions can lead to increased tree growth rates, potentially raising the site index. Conversely, in areas where higher temperatures lead to drought conditions, tree growth can be stunted, resulting in a lower site index. (Bernier et al. 1999, Ung et al. 2001). Non-climatic factors can also have an impact; these include defoliators, competition, availability of nutrients in the soil, tree position, age, and a number of other variables (Beaumont et al. 1999, Raulier et al. 2003). With the development of global climate model, climate estimation tools are become more widely used and available at each given site. Numerous studies have shown that climate is a reliable indicator of site productivity. In general, it is more efficient to use variables that indicate both temperature and moisture availability than to use just one of the two. To forecast site index across the Western United States, Weiskittel et al. discovered that the most efficient combination of 35 climatic variables was the interaction between growing degree days >5°C and the ratio of summer to total precipitation. Growing degree days have also been shown to be a useful indicator of productivity in other research (Farr and Harris, 1979; Ung et al., 2001; Hamel et al., 2004; Monserud et al., 2006). Additionally, climate change can exacerbate pest and disease outbreaks, which can negatively affect tree health and growth, further altering the site index. Therefore, climate change has a complex and region-specific impact on site index, reflecting the intricate interplay between climatic factors and forest ecosystem dynamics (Shore et al., 2006). since growing become concerned about the effects of global warming (Houghton et al. 2002) has increased the need to understand how climate affects key management variables like site productivity, which is essential for predicting growth and yield.
Research Objectives
Based on the background information, understanding the relationship between lodgepole pine site index and climate variables is important for forest management and growth and yield in future. And understanding how climate change will affect the Site Index helps us make recommendations for future forest management. Therefore, it is valueble to predict lodgepole pine site index in the entire Alberta in future based on the climate change. So, in this study, I want to know:
(1) Which climate variables are strongly correlated with site index and appear to drive variation in site index?
(2) What changes will happen to lodgepole pine site index as a result of climate change in Alberta?
With these two research questions, four objectives come up:
(1) Exploring the relationship between lodgepole pine site index and climate variables.
(2) Doing the Geospatial Site Index Modelling by random Forest method using the climate data of 2095 plots.
(3) Predicting lodgepole pine site index variability in 2025S, 2055S and 2085S under climate change based on using the climate data of whole Alberta.
(4) Comparing the difference between the predictions of managed stands' site index and natural stands' site index.