Dendroclimatic Studies : Tree Growth And Climat...
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Dendroclimatology is the science of determining past climates from trees (primarily properties of the annual tree rings). Tree rings are wider when conditions favor growth, narrower when times are difficult. Other properties of the annual rings, such as maximum latewood density (MXD) have been shown to be better proxies than simple ring width. Using tree rings, scientists have estimated many local climates for hundreds to thousands of years previous. By combining multiple tree-ring studies (sometimes with other climate proxy records), scientists have estimated past regional and global climates.
There are multiple climate and non-climate factors as well as nonlinear effects that impact tree ring width. Methods to isolate single factors (of interest) include botanical studies to calibrate growth influences and sampling of \"limiting stands\" (those expected to respond mostly to the variable of interest).
In general, climatologists assume a linear dependence of ring width on the variable of interest (e.g. moisture). However, if the variable changes enough, response may level off or even turn opposite. The home gardener knows that one can underwater or overwater a house plant. In addition, it is possible that interaction effects may occur (for example \"temperature times precipitation\" may affect growth as well as temperature and precipitation on their own. Also, the \"limiting stand\" helps somewhat to isolate the variable of interest. For instance, at the upper treeline, where the tree is \"cold limited\", it's unlikely that nonlinear effects of high temperature (\"inverted quadratic\") will have a numerically significant impact on ring width over the course of a growing season.
While the rendering and analysis of data from thermometer records largely suggest a substantial warming trend, tree rings from these particular sites do not display a corresponding change in their maximum latewood density or, in some cases, their width. This does not apply to all such studies.[2] Where this applies, a temperature trend extracted from tree rings alone would not show any substantial warming. The temperature graphs calculated from instrumental temperatures and from these tree ring proxies thus \"diverge\" from one another since the 1950s, which is the origin of the term. This divergence raises obvious questions of whether other, unrecognized divergences have occurred in the past, prior to the era of thermometers.[3] There is evidence suggesting that the divergence is caused by human activities, and so confined to the recent past, but use of affected proxies can lead to overestimation of past temperatures, understating the current warming trend. There is continuing research into explanations and ways to reconcile this the discrepancy between analysis of tree ring data and thermometer based data.[2]
Trees do not cover the Earth. Polar and marine climates cannot be estimated from tree rings. In perhumid tropical regions, Australia and southern Africa, trees generally grow all year round and don't show clear annual rings. In some forest areas, the tree growth is too much influenced by multiple factors (no \"limiting stand\") to allow clear climate reconstruction[example needed]. The coverage difficulty is dealt with by acknowledging it and by using other proxies (e.g. ice cores, corals) in difficult areas. In some cases it can be shown that the parameter of interest (temperature, precipitation, etc.) varies similarly from area to area, for example by looking at patterns in the instrumental record. Then one is justified in extending the dendroclimatology inferences to areas where no suitable tree ring samples are obtainable.
Tree rings show the impact on growth over an entire growing season. Climate changes deep in the dormant season (winter) will not be recorded. In addition, different times of the growing season may be more important than others (i.e. May versus September) for ring width. However, in general the ring width is used to infer the overall climate change during the corresponding year (an approximation). Another problem is \"memory\" or autocorrelation. A stressed tree may take a year or two to recover from a hard season. This problem can be dealt with by more complex modeling (a \"lag\" term in the regression) or by reducing the skill estimates of chronologies.
Abstract:Dendroclimatology and dendroecology have entered mainstream dendrochronology research in subtropical and tropical areas. Our study focused on the use of the chronology series of Masson pine (Pinus massoniana Lamb.), the most widely distributed tree species in the subtropical wet monsoon climate regions in China, to understand the tree growth response to ecological and hydroclimatic variability. The boosted regression trees (BRT) model, a nonlinear machine learning method, was used to explore the complex relationship between tree-ring growth and climate factors on a larger spatial scale. The common pattern of an asymptotic growth response to the climate indicated that the climate-growth relationship may be linear until a certain threshold. Once beyond this threshold, tree growth will be insensitive to some climate factors, after which a nonlinear relationship may occur. Spring and autumn climate factors are important controls of tree growth in most study areas. General circulation model (GCM) projections of future climates suggest that warming climates, especially temperatures in excess of those of the optimum growth threshold (as estimated by BRT), will be particularly threatening to the adaptation of Masson pine.Keywords: Pinus massoniana Lamb.; nonlinear; boosted regression trees; tree ring; general circulation model; subtropical area
The aim of the ACTI procedure is to identify and extract tree-growth-relevant climate drivers that are better explained by weather types than by temperature and precipitation. Therefore, the calculation of the ACTI is slightly more complex. While the frequency of each weather type hyj is simply the number of days (between June and August) of its occurrence, a statistical model is needed to calculate the influence (gj) that each weather type has on tree growth at a site to produce the ACTI. The following procedure is repeated for all four geopotential heights:
Interestingly, the SLP and temperature patterns associated with ACTI_1 and ACTI_2 highly resemble those associated with Eurasian summer heat waves of continental scale, as was found during the Russian heat wave in 2010 by Dole et al. (2011). Schubert et al. (2014) performed a rotated empirical orthogonal function (REOF) analysis on summer temperature and precipitation over northern Eurasia and suggested prominent spatial patterns responsible for regional heat waves and droughts. The ACTI_1 and ACTI_2 patterns highly resemble the second and first REOF patterns, respectively, found by Schubert et al. (2014). Schubert et al. (2014) suggest that their REOF patterns represent stationary Rossby waves emanating from eastern Europe to northeastern Asia, contributing to the heat waves and droughts over northern Eurasia. Therefore, resulting temperature and precipitation changes could affect tree growth over the study area. Potential impacts of these large-scale atmospheric waves on moisture variability, as inferred from the ratio of stable oxygen isotopes in tree rings, were recently identified for the southeastern Tibetan Plateau (Wernicke et al. 2017b).
Different growth-circulation response patterns were obtained for the higher-order modes, ACTI_3 and ACTI_4. Sites assigned to ACTI_3 were positively associated with SLP anomalies that extend diagonally from the Arabian Peninsula to northwestern Russia (Fig. 3k). At the 200-hPa level, a zonal structure with a low pressure center over northeastern China was visible (Fig. 3l). This structure is accompanied by positive associations of a southward-shifted subtropical jet stream extending from the Sahara to the Middle East to East Asia (Fig. 3m). This synoptic-scale circulation constellation is associated with growth-limiting conditions in the midlatitudes but with favorable conditions in southern Asia (Fig. 3n). Enhanced tree growth at the sites contributing most to the ACTI_4 mode is associated with below-normal SLP anomalies that originate from the northern and tropical Pacific (Fig. 3p). The most pronounced feature of ACTI_4 is its negative association with 200-hPa pressure anomalies over northeastern Russia (Fig. 3q), influencing the climate in this area, as well as in northeastern China and the Korea Peninsula (Figs. 3s,t). Although not strong, the overall pattern is reminiscent of the primary mode of the East Asian summer monsoon (Lau et al. 2000).
The leading tree-growth-relevant circulation patterns, that is, the ACTI modes, were compared to leading modes derived from summer H500 fields (Fig. 4). The first four H500 modes together explain 66.2% of the total variance, and simple correlation statistics showed that the corresponding pressure patterns were captured by the first four ACTI modes, explaining approximately 88% of the total variance (Table 1 and Fig. 4). ACTI_1 highly corresponded to H500_2 (r = 0.67; p < 0.001), ACTI_2 corresponded to H500_3 (r = 0.63; p < 0.001), and ACTI_3 corresponded to H500_4 (r = 0.24; p < 0.01), whereas ACTI_4 was negatively associated with H500_3 (r = 0.18; p < 0.05). The first three ACTI modes show temporally stable associations to the leading H500 modes over the last century (Fig. 4, right). Although the H500_1 mode exhibited the highest amount of explained variance (21.7%), trees show a negative but significant association with this pressure pattern. This observation is especially evident for the ACTI_3 and ACTI_4 modes, which together contained 84% of the circulation variability of H500_1 (Table 1). Interestingly, the other ACTI modes captured, to different extents, the leading circulation patterns. For instance, ACTI_1, ACTI_2, and ACTI_3 almost fully represent the H500_3 mode (Table 1). 59ce067264