Direct climate effects on tree growth in the Arctic

July 11, 2012, 8:33 pm
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This is Section 14.7 of the Arctic Climate Impact Assessment.
Lead Author: Glenn P. Juday; Contributing Authors: Valerie Barber, Paul Duffy, Hans Linderholm, Scott Rupp, Steve Sparrow, Eugene Vaganov, John Yarie; Consulting Authors: Edward Berg, Rosanne D’Arrigo, Olafur Eggertsson,V.V. Furyaev, Edward H. Hogg, Satu Huttunen, Gordon Jacoby, V.Ya. Kaplunov, Seppo Kellomaki, A.V. Kirdyanov, Carol E. Lewis, Sune Linder, M.M. Naurzbaev, F.I. Pleshikov, Ulf T. Runesson,Yu.V. Savva, O.V. Sidorova,V.D. Stakanov, N.M.Tchebakova, E.N.Valendik, E.F.Vedrova, Martin Wilmking.

The Flakaliden direct warming experiment

Background

In 1994, a soil warming experiment began at Flakaliden near Vindeln, 65 km northwest of Umeå, Sweden (64°07’ N, 19°27’ E). The experiment is in a planted Norway spruce forest established in 1963. The environment of the area is representative of the northern portion of the European boreal forest. Mean annual temperature is 2.3°C and mean annual precipitation about 590 millimeters (mm). The goals of the Flakaliden warming experiment are to:

  • quantify the effect of soil warming on the seasonal course of plant respiration and phenology of trees at low (irrigated) and high (irrigated and fertilized) availability of soil nutrients;
  • test and improve available mechanistic models used to project impacts of climate change on respiratory dynamics in plants and forest soils; and
  • to estimate net carbon budgets for boreal Norway spruce at the tree, stand, and regional scale, in present and future climates.

The soil warming treatment was installed in late 1994 in the buffer zone of one irrigated and one irrigated and fertilized stand; air temperature was not directly modified. Each heated subplot has a corresponding unheated control plot. The reason for using treatments including irrigation was to reduce the risk of drying the soil as an effect of the soil warming. The experiment was not designed to produce the effects of climate warming per se, but to isolate the effect of one of the most distinctive features of the boreal forest that is thought to contribute to its great carbon storage – soil temperature. While aboveground production of plant material is relatively great in boreal forests, cold soils limit the rate of decomposition that releases the fixed carbon back into the atmosphere. Therefore, soil warming, if it were to increase decomposition of stored soil carbon more than it affected production, could have a disproportionate effect on carbon balance.

In the Flakaliden experiment, soil warming starts in April each year, about five weeks before the soil thaws in the unheated plots. The soil temperature is increased by 1°C per week, until a 5°C difference between heated and control plots is reached. In late autumn, when the soil temperature in the control plots approaches 0°C, the soil temperature of the heated plot is decreased by 1°C per week. If the control plots do not freeze before 1 November, the temperature reduction is still initiated[9].

Questions, hypotheses, and results

Based on the assumptions of doubled atmospheric CO2 concentration and a 4 to 6 °C increase in annual mean temperature, the following responses were hypothesized:

  • Increased CO2 and temperature will have a small positive effect on biomass production in boreal forest growing on nutrient-poor sites. The stimulating effect will mainly be due to a shorter period with frozen soils and increased nitrogen mineralization.
  • Increased CO2 and temperature will have a positive effect on photosynthesis in boreal forest growing on sites with good nutrient availability. The net effect on biomass production will, however, be reduced as an effect of increased plant respiration (mainly foliage).
  • In boreal forests growing on poor sites, an increase in temperatures will stimulate soil respiration more than biomass production and therefore the net carbon balance will be negative until a new equilibrium is reached. The strength of the carbon source will depend on site index and the size of the soil carbon pool.
  • The boreal forest ecosystems will be a major sink for atmospheric carbon, once new equilibriums between carbon fixation and decomposition of soil organic matter have been reached. The time to reach a new equilibrium will depend on site index and the size of the soil carbon pool.

Soil moisture is not normally limiting to growth at Flakaliden[10]. The earlier spring soil thawing and later autumn freezing in heated plots increased mineralization of soil organic matter, which increased the concentration of most nutrients in the needles[11]. The effect was most pronounced during the first years of warming, but was still apparent after the fourth season, by which time stemwood production had increased by approximately 50% compared to the control plots[12]. Earlier access to water in spring results in an earlier start of photosynthesis[13]. After six seasons of warming at Flakaliden, stem volume production (m3/ha/yr) was 115% higher on heated and irrigated plots than on unheated control plots; on heated, irrigated, and fertilized plots production was 57% higher than on unheated plots. The results indicate that in a future warmer climate, with increased nitrogen availability and a longer growing season, biomass production is very likely to increase substantially on both low- and high-fertility sites in the more humid parts of the boreal forest[14]. However, the Flakaliden results are specific to soil warming without air-temperature change incorporated and it is too early to determine whether the observed responses are transitory or will be long-lasting.

In recent years, the large contribution of fine root turnover (growth and death within the growing season) as a factor in the annual production and storage of carbon in boreal forests has been recognized. Interactive effects of soil warming and fertilization on root production, mortality, and longevity at Flakaliden demonstrated that that nitrogen addition combined with warmer soil temperatures decreases the risk of root mortality, and annual fine root production is a function of the length of the growing season[15]. Under scenarios of climate change that increase soil temperature, and maintain adequate soil moisture and sufficient nitrogen, root production (and carbon stored in roots at a given time) in boreal forests is very likely to increase, especially at low-fertility sites.

The influence of soil temperature on boreal forest growth and carbon storage in natural field situations does not appear to be as great as the potential demonstrated in the Flakaliden results. After four years of warming, a major temperature acclimation had occurred and there was only a small difference in soil CO2 flux between heated and non-heated plots[16]. The timing of soil thawing (date of near-surface soil temperature rapidly increasing above 0°C) was not a good predictor for the start of spring photosynthesis in boreal coniferous forest at five field stations in northern and southern Finland, northern and southern Sweden, and central Siberia. The best predictor of the start of spring photosynthesis was air temperature[17]. In one case, photosynthesis commenced 1.5 months before soil thawing. At most sites a threshold value for air-temperature indices projected the beginning of photosynthesis in the spring, which varied among the sites by 30 to 60 days. The threshold values varied from site to site, probably reflecting genetic differences among the species and/or differences in the physiological state of trees in late winter and early spring induced by climate. A single physiological temperature threshold for the start of photosynthesis may not exist.

Climate effects on tree growth along the Central Siberia IGBP transect

The International Geosphere-Biosphere Programme (IGBP) is an international, interdisciplinary scientific research program built on networking and integration. It addresses scientific questions requiring an international approach, and undertakes analysis, synthesis, and integration activities on broad earth-system themes. The goals of the IGBP are to develop common frameworks for collaborative research, form research networks, promote standardized methodologies, facilitate construction of global databases, undertake model and data comparisons, and facilitate efficient patterns of resource allocation.

In the early 1990s, the IGBP developed the Global Change and Terrestrial Ecosystems project to establish terrestrial transects for global change research as one way to study ecosystem and climate change across large spatial scales[18]. The IGBP terrestrial transects run for more than 1,000 kilometers (km) along specific environmental gradients such as temperature or precipitation, and along more conceptual gradients of land-use intensity. They often cross ecotones such as tundra–taiga that are believed to be highly sensitive regions with strong feedbacks to global change. The Central Siberia IGBP transect was one of five high-latitude IGBP transects.

Climate response functions of trees along a latitudinal gradient

The geography of central Eurasia offers an excellent opportunity to examine how climate influences tree growth along an uninterrupted transect from the cold tundra margin in the north to the semi-arid steppe grassland of central Asia. This transect approach can provide some ideas about how climate change might affect growth by comparing the climate factors that historically and currently control tree growth as one proceeds southward. However, several limitations to this approach should be considered. For example, the genetics of individual trees of even the same species change from north to south. However, the comprehensive view of how tree growth responds differently to climate from cool to warm regions is still quite useful.

 

caption Fig. 14.16. Locations of tree samples along the Central Siberia IGBP transect (Yenisey meridian). See Fig 14.3b for vegetation and forest types along the transect.

 

To define the main climatic factors that influence tree-ring growth in various regions along the Central Siberia IGBP transect, correlation coefficients of tree-ring structure chronologies with monthly temperature and precipitation were calculated[19]. Tree-ring data from Siberian larch, Gmelin larch, Siberian spruce (Picea obovata), and Scots pine from 46 sites located in regions from the forest–steppe zone in the south to the forest–tundra zone in the north were used (Fig. 14.16). The relationship of tree-ring width to climate was investigated at all sites.

To strengthen the climatic signal common to each region, tree-ring data from sites were averaged as regional chronologies when sufficiently high correlation of master chronologies from the same vegetation zone permitted. Averaged regional chronologies were obtained for the following vegetation zones along the transect: forest–tundra and the northern part of the northern taiga; northern taiga; middle taiga; and southern taiga. These chronologies were compared to regional climatic data averaged for several meteorological stations. In the south, in the forest–steppe zone, the similarity of master chronologies was lower and three regional chronologies were obtained. They were correlated with the data from the nearest meteorological stations.

Comparison of the climatic response functions obtained for trees growing at different regions along the transect show that there is a change in the climatic factor that defines tree-ring growth at sites located along the temperature gradient in central Eurasia (Fig. 14.17). Summer temperature is one of the most important external factors that define tree-ring growth at the northern treeline[20]. It positively influences tracheid production and explains up to 70% of the variability in tree-ring width. In the middle taiga region, the effect of summer temperature on tree-ring growth decreases and the influence of precipitation increases[21]. In this region, winter precipitation has a strong negative effect on tree-ring growth, while June temperature has a positive influence. In the forest–steppe zone, tree-ring climatic response functions are typical of regions with limited moisture[22], where variability in tree-ring width is mainly explained by moisture variability (directly influenced by precipitation and indirectly influenced by temperature). The negative influence of spring and early summer temperature is explained by water loss from the soil at the beginning of growing season. High temperatures in the previous August and September affect soil water content, which is important for tree-ring growth activation during the next growing season[23].

 

caption Fig. 14.17. Statistically significant correlations between tree-ring increments and climatic variables (typical climatic response functions) for different vegetation zones of central Eurasia along the Central Siberia IGBP transect. Potential alternative outcomes of climate change are also depicted. A warmer climate could result in the replacement of existing forest vegetation zones in sequence (linear response) or novel ecosystems could appear (nonlinear response)[1].

 

From north to south along the transect, the limiting positive effect of summer temperature in the forest–tundra zone is replaced by the limiting effect of spring precipitation (positive) and early summer temperature (negative) in the forest–steppe zone (Fig. 14.17). Climate conditions (soil moisture and temperature) at the beginning of and during the first part of the growing season play the key role in determining annual radial tree growth and wood production at various latitudes from the northern treeline to the forest–steppe zone. Moving from north to south, the start of the tree-ring growth season shifts to earlier dates. June and July conditions are important for trees growing at the northern treeline, whereas April through June precipitation and temperature influence tree-ring formation in the forest–steppe zone (Fig. 14.17).

Under climate scenarios projected by the Arctic Climate Impact Assessment (ACIA)-designated models, trees currently growing in a given central Eurasian forest zone begin to experience temperatures near the end of the 21st century that are typical today of the next zone to the south. The simplest response (linear) would be for the propagules of the vegetation of any zone under consideration to migrate northward and eventually reconstitute the zone further north – in effect a "migration" of the zone northward through regeneration over time, so that present-day zones are replaced in the same sequence by the zones found to the south (Fig. 14.17). However, novel features of the ACIA-designated climate projections and their effects through time could bring about a nonlinear forest response (Fig. 14.17). It is difficult to make specific projections of these outcomes, but it is possible that some processes resulting from the ACIA-designated climate projections will produce unique effects not seen within the range of temperature variability experienced during the last millennium.

For example, all the ACIA-designated models project an increase in temperature that is very likely to result in thawing of permafrost along the southern limit of its present-day distribution (section 6.6.1.3) and in low-elevation basins in the southern Yukon, central Alaska, and southwestern portions of the Northwest Territories. Permafrost thawing would transform forest soils and create site conditions that have few or no current analogues. The ACIA-designated models project annual temperatures in the southern boreal forest of central Eurasia at the end of the 21st century that are typical of present-day temperate forest, but the actual amount of moisture supply and species migration could either permit or hinder development of temperate forest in this region. The current territory of southern taiga is projected to be replaced by forest–steppe[24] with a 15% phytomass decrease[25] in a warmer climate, and forest degradation and decline during the transition period are very likely to result in a major increase in forest debris and forest flammability. The difference between the ACIA-designated model projecting the largest increase in central Eurasian growing season temperature, generally the CGCM2, and the model projecting the smallest increase, the CSM_1.4, was generally between 15 and 20%. At the extreme upper range of temperature increases in the CGCM2 and the ECHAM4/OPYC3 scenarios, it is possible that warming and drying effects will bring tundra into contact with semi-arid steppe (Fig. 14.17). Empirical relationships between evapotranspiration and vegetation in central North America project that aspen parkland will extend into the Arctic[26] (Fig. 14.1) under a scenario based on doubled atmospheric CO2 concentrations.

Variability in the strength of climate influence on tree growth

Tree-ring variability in Gmelin larch, Siberian larch, and Scots pine was compared from sites located at different latitudes along the Central Siberian IGBP transect. Tree-ring width chronologies were calculated for trees from the forest–tundra zone (71° N); northern (64°–69° N), central (61° N), and southern (58° N) taiga regions; the forest–steppe zone (53° N); and high-elevation forest (51° N) (Table 14.6). To obtain comparable values of mean tree-ring width for different regions, only growth of mature trees (i.e., the period when the age trend in individual tree-ring width curves is not pronounced) was analyzed. The average age of larch trees growing in the south of the study area is less than that of northern larches. Hence, mean tree-ring width for larch from the north (61°–71° N) was calculated for the most recent 50 years for trees older than 200 years, and at the sites located at 57° to 51° N, for larch after 150 years of growth. Because pine trees are generally younger than larch growing at the same latitude, mean tree-ring width of pine was calculated for the most recent 50 years for trees older than 150 years.

Correlation coefficients of individual chronologies with the master time series and coefficients of sensitivity indicate the strength of environmental influences that synchronize tree-ring growth at the same site. The higher these two parameters, the greater the role of the environment in tree-ring growth. These statistics were averaged for the master chronologies obtained for sites from the same latitudinal belt.

Tree-ring width in larch trees increases from north to south up to the region of southern taiga (57° N; Table 14.6), then decreases in the high-elevation forest zone of Tuva (51° N). Correlation of individual chronologies with master time series and tree-ring sensitivity values indicate a decrease in environmental influence on tree-ring growth from north to south along the transect. The highest correlation coefficients were obtained for the northern treeline region and sites 200 km to the south, while the lowest were in the southern taiga region. Tree growth in the southern taiga region is less sensitive to environmental influences than growth of northern trees and trees at high elevations (Table 14.6). Similar changes in tree-ring variability along the transect were found for pine. Tree-ring width increases from the northern border of the pine area to the south taiga region. At the same time, the correlation of individual series with the master chronology and the sensitivity both decrease (Table 14.6). By contrast, in the forest–steppe zone (53° N) the year-to-year variability in pine growth is more closely synchronized to various local climate factors rather than an overall regional signal.

Table 14.6. Statistical characteristics of larch and pine ringwidth chronologies from different locations along the Central Siberia IGBP transect.

Latitude (° N)

Number of sites

Number of trees

Mean tree-ring width (mm)

Correlation with master chronology

Coefficient of sensitivity

Larch

71

4

48

0.19

0.8

0.42

69

3

55

0.21

0.82

0.4

64

7

71

0.24

0.67

0.34

61

5

78

0.37

0.66

0.28

57

3

28

0.53

0.58

0.21

51

4 and 3a

33

0.46

0.68

0.37

Pine

66

1

19

0.32

0.65

0.3

61

3

24

0.36

0.6

0.22

58

2

24

0.52

0.55

0.21

53

4 and 2a

16

0.62

0.65

0.32

aTwo samples at this latitude; the number of trees is the total for both sites

These trends in tree-ring width variability along the north–south Central Siberian IGBP transects repeated longitudinally are typical of tree growth in the entire Siberian boreal zone. Shashkin and Vaganov[27] reported similar results (increasing larch tree-ring width with decreasing site latitude) from Yakutia, East Siberia, caused by the gradient of environmental factors that most influence tree-ring growth. At the northern treeline, lack of summer warmth is the main climatic factor that limits ring growth[28]. As a result, at such high latitudes, large-scale patterns of summer temperature synchronize the growth of trees not only at the same site but also at sites located up to 800 km apart[29]. Temperature increases projected by the ACIA-designated models are very likely to have positive effects on larch growth across this area.

The influence of summer temperature decreases moving southward from the northern end of the transect. This gradient of environmental control leads to the higher growth rate and lower sensitivity of tree growth to climate in the middle of the transect. However, toward the southern portion of the transect, there is once again an increase in the correlation between individual tree-ring growth and sensitivity of master chronologies. Summer warmth in these dry regions is a strongly unfavorable factor for pine ring formation at its southern limit of distribution and larch at its lower elevation limit. Therefore, at the southern end of the transect, the strong influence of environmental factors on larch growth in high-elevation forest and on pine in the forest–steppe zone synchronize ring formation in trees on similar types of sites. The broadly shared environmental controls caused better registration of environmental changes in tree-ring structure (higher sensitivity) among sites. Temperature increases projected by the ACIA-designated models are very likely to have negative effects on larch and pine growth across the southern part of the transect.

Response of high-latitude conifers to climate and climate change scenarios

White spruce in Alaska and Canada

The scientific literature on the relationship of tree-ring width to climate in northern North America is dominated by studies of white spruce carefully selected in order to allow the reconstruction of past climates (section 14.6.2) from trees that achieve greater growth with warmer temperatures and lower growth with cooler temperatures. However, radial growth of white spruce on upland sites across a broad area of central Alaska exhibits a strong negative response to summer temperature[30] (Fig. 14.18). The negative relationship of radial growth to summer temperature is consistent throughout the 20th century, and occurs in a broad range of dominant and co-dominant trees in mature and old stands[31]. The growth of white spruce on these sites is best projected by the mean of May through August temperature in the year of ring growth and the year prior[32]. This relationship between climate and tree growth is sustained during the period of the instrumental record as well as the period for which summer temperatures were reconstructed from 13C isotope content and latewood density.

 

caption Fig. 14.18. Historic and reconstructed relationship between white spruce growth and summer temperature at Fairbanks, Alaska, and projections based on climate scenarios. The tree growth sample includes 10 stands across central Alaska. Summer temperature is an excellent predictor of white spruce growth. Because higher temperatures are associated with reduced growth and growth is the dependent variable, the temperature scale (left axis) has been inverted. Given the historical relationship between the variables and the scaling of these axes, the temperatures projected by the ACIA-designated models can be used to infer the approximate level of growth (right axis) possible in the future[2].

 

Based on this strong relationship, the two-year mean of May through August temperature for the Fairbanks grid cell was calculated from the ACIA-designated model and used to project future growth of this species on similar sites (Fig. 14.18). Because the relationship between temperature and growth is negative (less growth in warmer conditions) and the response variable of interest is tree growth, the temperature axis is inverted (increasing temperature downward) in Fig. 14.18.

The CGCM2 scenario projects the highest temperatures for the Fairbanks grid cell, although with a reduced range of annual variability. The CSM_1.4 scenario projects the least warming in the grid cell of the five ACIA-designated models, with variability similar to the recorded data (Fig. 14.18). If white spruce growth maintains the same relationship to temperature in the scenario period as during the calibration period, under the CGCM2 scenario growth is very likely to cease (the empirical relationship reaches zero growth) by the end of the scenario period (Fig. 14.18). Under the CSM_1.4 scenario, white spruce growth is very likely to decline to about 20% of the long-term mean. The zone of temperature and tree growth in Fig. 14.18 that corresponds to 20% or less of long-term mean growth has been highlighted as a "zone of probable species elimination". The stressed condition of trees in such a climate is likely to predispose them to other agents of tree mortality such as insect outbreaks (section 14.8) and diseases. While the CSM_1.4 scenario does not produce warming by the end of the scenario period that is empirically associated with zero growth, this white spruce population would be growing in a climate that is very likely to greatly reduce its growth. This climate and reduced level of growth almost certainly would place the trees that occur there now at an elevated risk of mortality, primarily from fire (section 14.9.2.3) and insects (section 14.8.2). White spruce in this region that demonstrate this climatic response are among the largest, most rapidly growing, and commercially valuable in boreal Alaska.

At high latitudes and altitudes where moisture is not limiting, white spruce has a positive growth response to summer temperature. The growth of near-treeline white spruce north of Goose Bay, Labrador in eastern Canada is positively correlated with the mean of monthly temperature in June, July, and September of the growth year and April of the previous year[33] (Fig. 14.19). Some of the trees in the sample may have been responding to non-climatic factors in the early 1950s and especially in the late 1990s when a significant short-term growth decline occurred (Fig. 14.19). The long-term tree-ring chronology available from the Labrador near-treeline sample reconstructs past climates in general agreement with those of several instrument-based and modeling studies of this sector of the North Atlantic[34].

 

caption Fig. 14.19. Historic relationship between white spruce growth and mean warm-season temperature (June, July, and September of the growth year and April of the previous year, smoothed with a 5-year running mean), and climate scenarios for central and northern Labrador, Canada[3].

 

If the relationship between temperature and tree growth in the Labrador sample is maintained in the future, the ACIA-designated model projections again provide a basis for evaluating possible tree growth responses. In the grid cell containing Goose Bay, the CSM_1.4 model projects the greatest amount of warming by the end of the scenario period and the GFDLR30_ c scenario projects the least warming. The longterm mean of ring-width growth in the sample is set to 1.0 and the variation is expressed in units of standard deviation (Fig. 14.19). As projected using the regression lines of the scenarios, the growth of trees that retained the historical relationship of temperature and growth would increase to about 0.3 standard deviations greater than the long-term mean under the GFDL-R30_c scenario and nearly 0.5 standard deviations greater under the CSM_1.4 scenario. Both scenarios produce warming and inferred levels of tree growth that this area has not experienced since the beginning of the proxy record in the late 1400s. These populations of white spruce are relatively small, slow growing, and generally not commercially valuable.

The response of treeline white spruce populations to climate change is of particular interest because this species delimits much of the North American treeline[35] and the performance under warmer conditions of present-day populations is an indication of the possible future effects of climate change. In a large (>1,500 trees) sample of treeline white spruce across the mountains of the Brooks and Alaska Ranges, over 40% displayed a statistically significant negative growth response to summer warmth while slightly fewer than 40% had a positive response to late spring warmth[36]. In the negatively responding (warmer = less growth) white spruce population, July temperature explained most of the variability in growth. Growth was strongly reduced at temperatures above a July threshold of about 16°C at the Fairbanks International Airport climate station, which served as a representative common reference (temperatures were estimated to be 3 to 4°C cooler at the various treeline sites). Growth of positive responders is correlated to March or April temperature, and the relationship is generally not significant until the second half of the 20th century[37]. D’Arrigo and Jacoby[38] found a similar dual response in white spruce in the Wrangell St. Elias Mountains of Alaska. A study of eight sites at and near alpine and arctic treeline in three regions of Alaska found mixed populations of temperature response types as well, and growth decreased in response to increasing temperatures at all but the wettest sites after 1950[39]. The negative growth response to temperature is more common in contiguous stands and tree islands (clusters of trees) than in isolated individual trees[40]. The intensity of the negative effect of July warmth increased after 1950, directly reflecting July temperatures above the threshold in a greater number of years in the second half of the 20th century compared to the first half[41].

The explanation for reduced growth in treeline white spruce with warming is that negative responders are experiencing temperature-induced drought stress, while the positively responding trees are not[42]. At some treeline sites in northern Alaska, individual trees have shifted their response to climate during their lifetimes, following the regime shift to warmer conditions that took place in the last decades of the 20th century[43]. Whereas previously the growth of the tree responded positively to summer temperature, it either became insensitive or began responding negatively to summer temperature after the shift to the warmer regime.

These results establish that from an ecological perspective, recent climate warming has been a major event that has strongly affected the growth performance of the majority of white spruce at and near treeline in Alaska and almost certainly in similar climate zones in Canada. The five ACIA-designated models project July temperatures by the mid- to late 21st century that the empirical relationship associates with very low or no growth in negatively responding white spruce. This suggests that under the ACIA-designated model projections, it is possible that the northern white spruce tree limit in Alaska and adjacent Canada would not readily advance. At the least, treeline is likely to become much more complex, with negative responders disappearing and positive responders expanding. It is possible that novel conditions would emerge, such as a portion of the southern tundra boundary in North America that is separated from the boreal forest by aspen parkland[44] (see Fig. 14.1). The actual response of treeline white spruce in this part of the world also adds support to the suggestion that aridification could be a major issue under climate scenarios projected by the ACIA-designated models.

Black spruce in Alaska and Canada

Stands dominated by black spruce represent about 55% of the boreal forest cover of Alaska and a large fraction of the northern boreal region of Canada. The response of black spruce to climate has not been studied as extensively or for as long as white spruce, so the literature on climate/growth relationships is more limited. This section draws on some recent dendrochronology work in Interior Alaska.

 

caption Fig. 14.20. Correlation of black spruce radial growth and Fairbanks mean monthly temperatures from four permafrost-dominated sites in central Interior Alaska. Lavender bars indicate a statistically significant correlation between the mean monthly temperature and tree growth, while blue bars indicate that the correlation is not statistically significant. Negative numbers preceding months on horizontal axis represent years before the year in which growth occurred[4].

 

Different temperature factors are associated with black spruce growth on different permafrost-dominated sites (Fig. 14.20), a more variable response than the consistent temperature/growth response in upland white spruce (White spruce in Alaska and Canada above). Of four sites examined, three show a negative growth response to increasing temperature, while one shows a positive response (Fig. 14.20). Both the Toghotthele site (Fig. 14.20a) and the Zasada Road 10 site in the Bonanza Creek Long Term Ecological Research site (Fig. 14.20c) show a negative growth response to summer temperatures (year of growth and 2 years prior). Radial growth of black spruce at both the northern and southern BOREAS sites in western Canada was also negatively related to summer temperature, or conversely, favored by cooler and wetter conditions[45].

Black spruce at the Caribou-Poker Creeks Research Watershed (CPCRW) show both a negative correlation to April and May temperatures during the growth year and a positive correlation to February temperature two years prior to growth (Fig. 14.20b). A simple two month index of the mean of April and February temperature is highly correlated to the growth of the CPCRW trees (Fig. 14.21). The negative effect of warm early-spring temperatures on growth at CPCRW can be attributed to the onset of photosynthesis in spring when the ground is still frozen, causing desiccation and damage to the needles[46] early in the growing season. The smoothed (5-year running mean) values are highly correlated during the 20th century (r=0.86), suggesting that tree growth of this species at sites similar to these could be projected using the ACIA-designated scenarios. While warm February temperatures favor growth, warmth in April depresses growth. With substantial temperature increases in the late 20th century, growth of this species has declined because the negative influence of April is stronger.

 

caption Fig. 14.21. Relationship of radial growth of black spruce at Caribou-Poker Creeks Research Watershed to the mean of April (growth year) and February (two years prior) temperature, smoothed with a 5-year running mean[5]. Temperature axis is inverted as in Fig. 4.18.

 

Growth of black spruce trees at Fort Wainwright is positively correlated with winter temperatures (Fig. 14.20d). When January in the year of growth and December, February, and January in the year prior to growth were all warm, the trees grew better (Fig. 14.22). The smoothed (5-year running mean) values are highly correlated during the 20th century. This is one of the few species and site types in central Alaska for which the empirically calibrated growth rate can be inferred to improve under projected higher temperatures.

 

caption Fig. 14.22. Relationship of radial growth of black spruce at Fort Wainwright, Alaska (n=20 trees), to a 4-month climate index (mean of monthly temperature at Fairbanks, Alaska, in January of growth year and January, February, and December of previous year). Scenario lines show projections of the 4-month climate index[6].

 

The positive relationship between monthly temperatures and black spruce growth at the Fort Wainwright site suggests that growth of trees on sites similar to it is very likely to increase (Fig. 14.22). The ECHAM4/ OPYC3 model projects especially strong warming for the Fairbanks grid cell in the winter months that best predict black spruce growth at the site, so the empirical relationship, if it were maintained, suggests a major increase in growth rate (Fig. 14.22). Black spruce at the Fort Wainwright site occupy a low productivity system, so the overall significance of the projected growth increase is not clear. The CSM_1.4 model projects winter temperatures that do not increase as rapidly or to as great a degree, so the modeled relationship of these positively responding spruce suggests only a modest increase in growth under that scenario. Presumably, the positive effect of warm winter temperatures on growth is experienced though control of active-layer rooting depth and soil temperature in this permafrost-dominated ecosystem. However, well before the end of the scenario period, the CGCM2 (Fig. 14.9) and all the other models project mean annual temperatures above freezing in this grid cell. If temperatures increase to that extent, the temperature/growth relationship depicted in Fig. 14.22 is not likely to persist. However, this permafrost site is very near thawing, and warming of the magnitude projected by the ACIA-designated models would probably initiate thawing during the 21st century, leading to widespread ground subsidence and tree toppling, representing a new challenge for the survival of this species on such sites. Once the soil thawing process is complete, species with higher growth rates than black spruce, such as white spruce or paper birch, are likely to have a competitive advantage on the transformed site.

For the Toghotthele site (Alaska Native-owned land; Toghotthele Corporation), model projections of future temperature were compared to the empirical record of black spruce growth (Fig. 14.23) similar to the approach used for white spruce (White spruce in Alaska and Canada above). The mean of four summer months is an excellent predictor of tree growth, with warm years resulting in strongly reduced growth. As for white spruce, the results suggest that if climates similar to those projected by the ACIA-designated models actually occur, by the end of the 21st century black spruce would experience climates that are very unlikely to permit the species to survive on similar types of sites. In this case, the CSM_1.4 model projects the highest levels of the particular set of monthly temperatures that drives the relationship while the CGCM2 model projects slightly lower levels. However, in both scenarios, warmth in individual years produces an empirical relationship very near zero growth before the end of the scenario period. Allowing for some differences in calibration and degree of climate control, the generally similar growth of black spruce in the BOREAS study areas suggests that elimination of black spruce is very likely to be widespread across the western North American boreal forest.

Scots pine in Scandinavia

 

caption Fig. 14.23. Relationship between summer temperatures(mean of May and June in growth year, and June and July of the previous year) at Fairbanks and relative growth of black spruce at the Toghotthele site in central Alaska, and projections based on climate scenarios[7]. Temperature axis is inverted as in Fig. 14.18.

 

Growth responses of Scots pine at the tree limit in the central Scandinavian Mountains varied throughout the 20th century[47]. Long, hot, and dry summers have traditionally been thought to be optimal for pine growth in that environment. The greatest pine growth of the past three centuries occurred during the decade from 1945 to 1954. Although summer temperature was not particularly high during the mid-20th century, higher than average spring and autumn temperatures that extended the growing season were inferred to be the cause of this decade of high Scots pine growth[48]. Despite similar apparently favorable temperature conditions in the latter part of the 20th century, growth of this species on similar sites declined during the most recent warmth. This suggests the occurrence of some additional unique component of the recent warming that negated the previously positive influence of extended growing seasons.

 

caption Fig. 14.24. Location of 14 Scots pine ring-width chronologies (see Table 14.7 for key to locations).

 

In addition to north–south transects of tree-ring chronologies, an east–west transect has been developed in Fennoscandia[49]. Nine tree-ring width chronologies for Scots pine were compared for growth variability and response to climate along a gradient of maritime to continental conditions in central Fennoscandia. The study revealed higher growth variance and stronger response to climate in the oceanic area west of the Scandinavian Mountains, compared to the more continental areas further east. Pine growth responded positively to elevated summer temperatures in the western areas, and positively to high summer precipitation in the east. Generally, pine growth showed a weaker relationship with the North Atlantic Oscillation (section 2.2.2.1) than with temperature and precipitation. During the last half of the 20th century, pine growth in western Fennoscandia displayed reduced sensitivity to climate, while in the east, growth sensitivity increased. Indications of growth stress were found in one site east of the Scandinavian Mountains. Increasing temperatures have been accompanied by increasing precipitation in Fennoscandia throughout the 20th century, and it was suggested that a change in climate regime from subcontinental to sub-maritime caused those trees to experience climatic stress[50].

A selection of Scots pine tree-ring width chronologies was collected from across Sweden (Fig. 14.24). The standardized chronologies include wet (peatland) and dry (mineral soil) growth environments (Table 14.7). Despite large differences in climate responses among the sites, the collective growth trend for all the sampled Scots pine in the last few decades of the 20th century is negative (Fig. 14.25). Furthermore, a common feature is distinct changes in growth sensitivity to climate at all sites during that period, a feature that has also been observed at several other Fennoscandian sites. The pattern is one of widespread and simultaneous decreases in growth, and a decreased ability of previously established climate factors to project growth as accurately.

Table 14.7. Locations of 14 Scots pine ring-width chronologies. First column shows abbreviations used in Figs. 14.24 and 14.25.7 for key to locations).

 

Location

Site type

N

Nikkaluokta

dry

AJ

Angerusjärvi

wet

LY

Lycksele

dry

T

Stortjäderbergsmyran

wet

J

Jämtland

dry

ÅÖ

Årsön

wet

TS

Tannsjö

dry

SK

Skuleskogen

dry

NO

Norberg

dry

BM

Bredmossen

wet

SH

Stockholm

dry

HM

Hanvedsmossen

wet

GH

Gullhult

dry

AM

Anebymossen

wet

 

caption Fig. 14.25. Standard chronologies of Scots pine ring width (age de-trended and normalized with long-term mean set to 1.0 and standard deviation on 1.0) in Sweden. Curves express the degree of growth at any time relative to the long-term mean of the sample (see Table 14.7 for key to locations)[8].

 

Because precipitation, in addition to temperature, has increased over the past decades in Scandinavia, it is unlikely that drought stress is the main reason for decreasing Scots pine growth throughout Sweden. The one exception is northernmost Sweden, where growth responses to summer temperatures are decreasing and responses to autumn precipitation increasing. However, in central Sweden, the evidence suggests a different cause of reduced growth and changing climate responses. On the eastern slopes of the Scandinavian Mountains, the climate could be regarded as subcontinental, with low annual precipitation and high temperature amplitude over the year. Tree-ring data from sites east of the mountains implies that over the past decades, the climate of this area has become more maritime, and consequently the trees may have suffered stress from surplus moisture rather than drought[51]. In conclusion, the observed change in tree growth patterns and growth/climate relationships is most likely an effect of contemporary climate change. How trees respond to increased temperatures and/or precipitation is dependent on the local climate, and it seems that trees in oceanic areas are less affected than are those where the local climate regime has shifted from subcontinental to sub-maritime.

 

Chapter 14: Forests, Land Management, and Agriculture
14.1. Introduction
14.2. The boreal forest: importance and relationship to climate
14.3. Land tenure and management in the boreal region
14.4. Use and evaluation of the ACIA scenarios
14.5. Agriculture
14.6. Tree rings and past climate
14.7. Direct climate effects on tree growth
14.8. Climate change and insects as a forest disturbance
14.9. Climate change and fire
14.10. Climate change in relation to carbon uptake and carbon storage
14.11. Climate change and forest distribution
14.12. Effects of ultraviolet-B on forest vegetation
14.13. Critical research needs

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  50. ^ Ibid
  51. ^ Ibid

 

 

 

 

Glossary

Citation

Committee, I. (2012). Direct climate effects on tree growth in the Arctic. Retrieved from http://www.eoearth.org/view/article/151734

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