The purpose of this project is to analyze which climatic changes could potentially affect tree lines and which factors of change make a significant difference. The tree line changes for this project’s purpose are defined as density, altitude, and elevation of the forests. Information is provided by studies in multiple parts of the world over but focusing on Northern Europe and West Africa. The location of the forests in such various areas adds to the effectiveness of this study because it gives a variety of species and the climates in which they grow.
The climatic changes included in this project were chosen based on amount and accuracy of information found relating to the change and the factor’s relevance to not only tree lines but also tree ring growth (which was limited). The factors included are the effects of temperature, vegetation, El Nino Southern Oscillation events (ENSO)*, Sea Surface Temperatures (SST), and precipitation rates. Data from each site has room for error due to unavoidable or immeasurable events, most commonly human interference.
*ENSO is a sudden change in pressure, winds, and rainfall near the Indian Ocean and parts of the Pacific. The changes cause droughts, floods, and other extreme climate changes.
The forest locations used in this project are vast and climatically diverse. It would be expected to have several different factors affecting each area of forest due to such different conditions; however that was not the case. All areas were potentially affected by vegetation; however different locations took into account more specific factors. Temperature reconstructions for all articles were based on dendrochronology (the study of tree ring growth). Each sample date is calibrated based on the year 1950, which means that each date given is written as cal. year BP (calibrated year before present) with present representing 1950.
The sample sites in West Africa were located on the Ivory Coast (Comoé National Park, CNP ) and in the central western part of Benin (upper Oué mé catchment, UOC ) and focused heavily on precipitation factors, especially due to SST and ENSO. Both sites experience a rainy season (from April to October) and a dry season (November to March). This regions has a more tropical climate, so dating the trees is more difficult but still accurate. The visibility of annual tree ring growth is limited with tropical trees. Due to this, climate reconstruction in this region was attained through cambial wounding (measuring "injuries" of tree trunks and their re-growth), radioactive dating, stable isotopes, and dendrometers (bands around trees that record growth as accurately as hourly). The subsurface of the landscape consists of granite or gneiss. Because of the semiarid and sub humid location, a concern in the hydrological cycles (water distribution and quality).
The area of this study was diverse because it was over such a great region ( map ). Each slope side had potential for different results due to vegetation, weather, and population. The slope difference in the Alps played a major role in this analysis and remained the focus of the article. North facing slopes experienced a delay in snow melting and vegetation was severely different. Along with cooler climates destruction of the slope was due to more natural causes, such as avalanches. However, the South facing slopes had more human interactions, specifically deforestation, due to a warmer temperature and easier living conditions. Although trees grow higher in elevation on the drier North slope, the front ranges of the South slope climb higher up the mountain. Because of the differences it was important that an accurate data set of the whole mountain range was obtained. Pollen analysis also shows events that change tree lines. When there are trees at a higher level that have higher pollen production, growth may be skewed. By studying pollen movement, there is evidence that the increase of pollen on the lower trees helps boost growth. Changes in growth (by measuring tree rings) can be seen through pollen analysis, which can be correlated with climate and other surrounding facotrs.
Located in the subarctic climate,( map ) this study has the most consistent temperature comparison. Because it varies a little, average July temperatures are used to determine the factors of tree line growth. Although this region is much farther north, the bedrock of this area is similar to that in Africa, made mostly of granite and gneiss. Isostatic uplift (earth’s way of maintaining a balance between the asthenosphere and lithosphere when there is a change in pressure and force on the surface, due to lower sea levels, glaciers etc.)* of this area played a part when reviewing data of the region. During glaciations the tree line is lower because the asthenosphere gives to even the surface out. Pine, spruce and birch trees were used for this study. The tree line of each species in this area can be categorized by elevation (with exceptions). The pine trees have an altitudinal limit of 380 meters (conifer limit), while the spruce trees sit just above that. Spruce tree growth depends heavily of properties of soil, pH, and hydrological cycles.
*The lithosphere is the crust and upper mantle of the earth. It is hard and brittle, and therefore easily shifts and cracks. The asthenosphere is the upper part of the mantle below the lithosphere, it is under higher heat and pressure making it more ductile which enables it to keep isostatic balance.
The use of GIS in these studies was most important to determine the definition of a forest and what the actual measurements of tree lines are. To define a forest, blocks of areas were broken up in 100 sq. m. (10 x 10 meters) sections. A forest is generally determined by two main factors: tree height to be at least three meters and canopy area coverage (specifically twenty percent for areas greater than fifty meters wide, and 60% for areas twenty-five to fifty meters). This is done by taking aerial photos (of ten kilometer sections) and overlaying them onto a grid map. Using GIS, vegetation , soil , slope, population, glacial advances, elevation, altitude, temperatures , and bedrock is mapped and coded. The elevation of the highest tree is dubbed as the ‘GIS Tree Line’ and tree lines are only calculated is it is at least 1750 meters and if the actual tree line is 150 meters above the GIS Tree Line. The difference on elevation between the GIS Tree Line and the actual tree line helps counteract mountain tops laden with forests, wind and lower peaks. [ Figure One Swiss Alps] As the forest covered area increases, the overestimation of tree lines decrease. [ Figure Two Tree Line Accuracy]
Setbacks in finding forest areas cannot be avoided. However, they do not seem significant enough to skew results. Areas within the ten meter sections that have heavy forest but retain spots with little or no trees overestimate the density of trees. Other inaccuracies include measuring a specific point, rather than the top tree line.
Here is a link to an example of how GIS is used to study trees. This site is run by the Swiss Federal Institute for Forest Snow and Landscape Research. It is updated monthly (from what I gather is is written in a few different languages, but there was one german page), and compiles research from multiple research institutes from all over the world.
In each study different factors are taken into account over others depending on location of the forests. However, temperature, precipitation and human interference affected all areas of study. It is next to impossible to find an area of forest undisturbed, either naturally or unnaturally. Each region was tainted through human interference, due to deforestation, farming, and population growth. However, each different area also had its own unique climatic changes. The northern, colder forests experienced avalanches, glaciers, snow, etc. but the southern forests experienced affects off of the oceans. During El Niño events (warm ENSO phases) there was reduced rainfall, slowing the growth of trees, and during La Niña events there was increased precipitation. However, because both altering events of ENSO occur, simply put, they cancel each other out and the determining factors of temperature and precipitation remain.
The same factors played into the northern forests. The slopes of the mountains were thought to be a determining factor in tree line changes. However, because of the climate variations and GIS the slope has no affect on tree lines. Climate and precipitation, however, remained important. There was an intense time, "Medieval Warm Period" where tree growth was boosted because of the warm, wet weather and slowed promptly after during the "Little Ice Age" where they experienced drier, colder climates.
Dendrochronology is our most accurate study of climate change. By studying the past we can learn about the future. And by studying what affects trees we can learn more and more about them. Scientists are eliminating factors that produce drastic changes so we can stay focused on what will change. We need trees for a multitude of reasons, from natural resources, to a breath of fresh air. Their climate reconstruction is so accurate that to track upcoming events is easier every day. By seeing the affects that La Niña and El Niño had on tropical trees we can predict these events by monitoring the growth.
The study of tree growth does not solely depend on location (therefore) climate, but goes much deeper into the bedrock, soil, or which side of the mountain it sits on. All these factors can help us relate one forest to another (such as Africa and Europe having the same granite make-up but opposing climates). The geographic information systems make these studies easier by letting us layer our maps with one slice of valuable information on top of another. This way we can see what changes are significant and which we can brush off.
I chose a topic very relatable to my interests of geology and climate change. The most difficult part of this assignment was finding articles that not only related to each other, but to GIS. I started out with several and after reading some of them I realized that I was looking at a study too far off topic, or one that did not incorporate GIS. I had to change my topic focus more than once, and finally decided on showing how the study of trees in different areas can be related.
The articles I ended up with laid out in detail how to use GIS to map the areas, but finding actual GIS data was extremely difficult. Most websites boasted they held the information I needed, and then told me I had to pay $24.95 just to see it. I found some good maps to use to get an idea of what the GIS data would look and feel that the explanation of how to use GIS was sufficient.
The list of my sources.
