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Tree Advancement Patterns
- 1. TREELINE ADVANCE PATTERNSOF ALASKAN WHITE SPRUCETREELINE ADVANCE PATTERNS OF ALASKAN WHITE SPRUCE Keena Auld, Kenneth Chadwell, Turner Glasgow, David Cairns, and Keith Gaddis Texas A&M University Department of Geography, College Station, Texas Is P. glauca treeline advancing? Question Hypothesis 1. If treeline is advancing, trees establishment date will decrease (become more recent) as elevation increases 2. If treeline advance is not occurring, then there will be no relationship between elevation and tree establishment date Methods Lab Methods In the fall of 2015, we measured the establishment date of each tree by counting the tree rings on extracted tree cores. Abstract Many recent studies have indicated altitudinal treeline advance throughout the world due to global climatic changes. These advances have major implications for the assembly and survival of species throughout the world that may become marginalized as their habitat is destroyed by this advance. Given this fact, we set out to examine treeline advance patterns in the dominant North American treeline forming species, white spruce (Picea glauca) throughout south-central Alaska. We examined Dendrochronological data rom 17 sites and have found a variable arrangement of treeline pattern across the study area with some sites showing a clear pattern of advance and others maintaining stabile over the recent past. Background Treeline is an ecotone where the forest biome transitions to a tundra at the highest elevation point where trees can grow Changes in climate have a direct link the global treeline position. Long winters limit establishment of seeds and permafrost prevents deep roots from penetrating the soil. As global climates have warmed, forest biomes have began to encroach on that of the tundra leading to treeline advance. Study System White spruce (Picea glauca) is native to the boreal forest of North America. It has evergreen needles accompanied by narrow, oblong cones. The species disperses through seeds or layering (where lower branches take root to form new trunks that later separate from the maternal tree forming a clone). The area used in this study was south- central Alaska. The climate of region is subarctic with temperatures averaging -12 to 18 ˚C throughout the year. Climatic data has indicated a warming trend in this area. This region is heavily forested, with high mountainous terrain. Results Conclusion Treelines are advancing • 5/17 show definite treeline advance • 3-6 sites show younger trees at treeline • Recent advance over a short spatial scale Topography determines advance • The correlation between tree age and distance from treeline was explained by the slope at the sample site. • Low sloped sites have greater treeline advance rates. Acknowledgements Future Work How does climate influence advance? • We will determine if contemporary climate to influence advance rates. • We will use climate modelling to identify if areas with greatest climatic change have experienced greater advance. • We will analyze additional topographic variables (slope, aspect, curvature) How do dispersal and reproduction affect influence treeline advance? • We will relate this work to our existing analysis of dispersal and reproductive pattern using genetics. Treeline Advance Infilling No Pattern We would like to thank Rachel Clausing, Zac Harlow, and Michelle Lee for tireless field collection. Clint Magill provided guidance and laboratory resources to conduct genetic work. Parveen Chhetri assisted in lab work and analysis. 1840 1860 1880 1900 1920 1940 1960 1980 2000 2020 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 16 P-value > 0.05 1900 1920 1940 1960 1980 2000 2020 2040 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 20 P-value > 0.05 1750 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 25 P-value > 0.05 1900 1920 1940 1960 1980 2000 2020 2040 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 28 P-value > 0.05 1750 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 32 P-value > 0.05 1750 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 33 Adjusted R-squred: 0.08 P-value < 0.05 1450 1550 1650 1750 1850 1950 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 34 P-value > 0.05 1860 1880 1900 1920 1940 1960 1980 2000 2020 2040 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 41 Adjusted R-squred: 0.27 P-value < 0.001 1650 1700 1750 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 36 Adjusted R-squred: 0.10 P-value < 0.05 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EStablishmentYear Distance From Treeline (m) Site 43 P-value > 0.05 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 46 P-value > 0.05 1650 1700 1750 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 55 P-value > 0.05 1900 1920 1940 1960 1980 2000 2020 2040 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 58 Adjusted R-squred: 0.25 P-value < 0.001 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmnetYear Distance From Treeline (m) Site 68 Adjusted R-squred: 0.28 P-value < 0.001 1860 1880 1900 1920 1940 1960 1980 2000 2020 2040 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 71 P-value > 0.05 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 75 Adjusted R-squred: 0.19 P-value < 0.001 1650 1700 1750 1800 1850 1900 1950 2000 2050 0 100 200 300 400 500 600 EstablishmentYear Distance From Treeline (m) Site 76 P-value > 0.05 Field Methods In the summer of 2015, we sampled cores from trees spaced on 500 m transects parallel and perpendicular to treeline. Five trees were sampled every 50 m. We collected a total of 1,870 white spruce tree cores across 17 sites. Analysis We used linear regression to examine the age of trees relative to the distance from treeline. An additional analysis examining topographic effects was conducted using logistic regression y = 0.0569ln(x) + 0.0805 R² = 0.3586 -0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 CorrelationCoefficient(r) Slope of Sample Site Does topography influence treeline advance ? We conducted a preliminary analysis to examine topographic effects (slope at each sample site) on treeline advance, using a logistic regression.