Blue Reflectance (BLU), a new inexpensive shortcut towards robust tree- ring based climate...
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Blue Reflectance (BLU), a new inexpensive shortcut towards Blue Reflectance (BLU), a new inexpensive shortcut towards robust tree-ring based climate reconstructions? robust tree-ring based climate reconstructions? Jesper Björklund, Kristina Seftigen and Hans Linderholm Jesper Björklund, Kristina Seftigen and Hans Linderholm Department of Earth Sciences, University of Gothenburg, Sweden Introduction Introduction In Paleoclimatology, tree-rings is used for climate reconstructions on annual to multi-millennial scale. Methods to extract information from trees are for example measurements of ring-width (TRW) or density of the wood i.e. Maximum Density (MXD). Historically, MXD has proved to be an excellent proxy for warm season temperatures in cooler climates (Schweingruber et al. 1988). However, X-ray of tree-rings is time-consuming and expensive. Furthermore, for tree- rings to robustly represent climate variability on longer timescales, the number of trees required greatly increases (Briffa and Melvin 2008) and production rates and costs can become a significant obstacle. Recently, reflected blue light from optically scanned images has been explored to investigate if this is a viable shortcut to robust warm season temperature reconstructions (e.g. McCarrol et al. 2002; Campbell et al. 2007). The parameter that that is measured is the minimum value of reflected blue light in every annual increment henceforth abbreviated (BLU). Previous studies have shown that BLU and MXD are highly correlated on annual to decadal scale. Now Results and Discussion Results and Discussion Study Area Study Area Methods Methods Figure 1. The fore fell Bårgå where dead and living trees were collected at the tree-line Figure 5. MXD plotted against different chronology configurations of the BLU data. Notice the increased coherence with more complex BLU chronology configuration. This is not a sustainable way of producing BLU chronologies in future work beacuse there are also nuance differences between deadwood. A correction for nuance differences is needed to move forward with BLU on species that have heartwood/sapwood of this kind. A new site in Northern Sweden 50 km north of the town of Arjeplog was sampled for Scots Pine (Pinus Sylvestris L.). Coordinates: Lat. 66° 17’ 37’’ N, Lon. 18° 14’ 59’’ E. The source area for the sampled trees was a north-facing slope on an 800 m high fore fell, Bårgå (Fig 1) where the pines form the tree-line at 700 m a.m.s.l. For direct comparison of BLU vs. MXD, the same cores of wood were analyzed for both variables. The samples were prepared according to standard dendrochronological techniques (Schweingruber et al. 1978). Resins and extractives were chemically removed with ethanol in a Soxhlet extraction apparatus. The X-Ray was performed using an ITRAX multiscanner from Cox Analytical Systems (www.coxsys.se ). The BLU was produced with a flatbed Scanner Epson Perfection V600 Series calibrated with SilverFast Ai professional scan software, standard protocol was followed according to Campbell et al. (2011). The raw MXD and BLU was standardized to remove age related trends in the series with Regional Curve Standardization (RCS; Briffa et al. 1992). This to enable comparison of chronologies on longer time scales than the mean age of the trees Cook et al. (1995). The BLU chronology was named BLU Original . Figure 2. Top sample: living tree not alcohol refluxed, middle sample: living tree refluxed with alcohol for 24 h, bottom sample: dead tree refluxed in alcohol. Notice the nuance difference between the living and the dead refluxed trees. Scots Pine has a pronounced difference in color between sapwood and heartwood (Fig 2). This color difference can not entirely be removed in extraction with alcohol. To account for this, a second BLU chronology was made which consisted one heartwood and one sapwood chronology, named BLU Heartwood/Sapwood . The sapwood chronology’s mean and variance was adjusted to fit the BLU heartwood chronology. A visual inspection of samples also revealed a distinct difference between heartwood from living and dead trees (Fig 2), and a third chronology was produced using similar division ans in the previous chronology and named BLU Deadwood/Heartwood/Sapwood . The mean and variance from the living tree heart wood chronology was adjusted to the dead tree heartwood chronology and finally the sap wood to the mean and variance of the combined “dead-living” composite chronology. During the overlap between the different chronologies the sample depth is varying, diminishing in the ends of each chronology hence replication weighted averages between the z-scored chronologies was made, see figure 3 for overlap. First differenced MXD and BLU series have a correlation of r = 0.80 (n = 19 456) and the chronologies have a correlation of r = 0.95 (n = 810, Fig 4). Examining the common variability visually on longer timescales, the MXD and BLU Original covary excellently from 1200 A.D. to 1700 A.D. (Fig 5). After this there is a dramatic divergence. Examining the MXD and BLU Heartwood/Sapwood this divergence is reduced but there are still profound dissimilarities (Fig 5). Examining the MXD BLU Deadwood/Heartwood/Sapwood all centennial scale divergence is removed but the chronologies have a slight overall difference in trend (Fig 5). The BLU method is interpreted, from these results to be substantially more sensitive to the discoloration from waste products and resin in the heartwood and sapwood. Likely the longer waste products and resin reside in the wood, the more permanent and pronounced the discoloration becomes (Fig 2). One way of overcoming this vital weakness in BLU could be to quantify the background Blue reflectance caused by resin discoloration in the early wood of neighboring rings and, assumed that the latewood have the same background discoloration, remove this from BLU and make a new proxy. The difference in latewood and ambient early wood blue reflectance (δBLU) would enable samples with heavy discolorations to be used together with samples with little discoloration. And also ensure multi-centennial or even multi-millennial scale variability. If this drawback can be resolved it is clear that the value of BLU is tremendous since the climatic signal is equal in type, strength and field to MXD (Fig 6). Since flatbed scanners, for example the one used in this study costs roughly thousand times less than the X-Ray machine used in this study, and the time of producing the BLU data was roughly half of the time of producing MXD data, the need for tweaking this proxy for optimum performance is of great value. Figure 3. Expressed population signal, a measure of chronology confidence. EPS below 0.85 is considered to low for reconstructions. Sample depth through time where overlap of deadwood, living tree heartwood and sapwood is shown. Figure 4. Scatter- plot with the relationship between first differenced MXD and BLU on series level in black and on chronology level in red. Figure 6. Spatial correlations between MXD on left and BLU on rihgt with April-August Temperatures. The correlations were made on first differenced data. The star in each plot is the sampling site Bårgå, Arjeplog Sweden. Conclusion Conclusion Briffa et al. (1992) Clim Dyn. 7:111-119; Briffa and Melvin (2011) In: Hughes M K, Diaz H F, Swetnam T W(ed), Dendroclimatology: Progress and Prospects, Springer Verlag, pp 378; Campbell et al. (2007) The Holocene 17:821; Campbell et al. (2011) Tree-ring Research 67:127-134; Cook et al. (1995) Holocene 5:229-237; McCarroll et al. (2002) Arctic, Antarctic and Alpine Research 34:450-453; Schweingruber et al. (1988) Boreas 17:559-566; Schweingruber et al. (1978) Tree-ring bull. 38:61-91 Acknowledgements This work was supported by Vetenskapsrådet and Formas (grants to Hans W Linderholm) The poster contributes to the Swedish strategic research area Biodiversity and Ecosystem services in a Changing Climate (BECC). References References
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Transcript of Blue Reflectance (BLU), a new inexpensive shortcut towards robust tree- ring based climate...
Blue Reflectance (BLU), a new inexpensive shortcut towards robust tree-Blue Reflectance (BLU), a new inexpensive shortcut towards robust tree-ring based climate reconstructions?ring based climate reconstructions?Jesper Björklund, Kristina Seftigen and Hans LinderholmJesper Björklund, Kristina Seftigen and Hans LinderholmDepartment of Earth Sciences, University of Gothenburg, Sweden
IntroductionIntroductionIn Paleoclimatology, tree-rings is used for climate reconstructions on annual to multi-millennial scale. Methods to extract information from trees are for example measurements of ring-width (TRW) or density of the wood i.e. Maximum Density (MXD). Historically, MXD has proved to be an excellent proxy for warm season temperatures in cooler climates (Schweingruber et al. 1988). However, X-ray of tree-rings is time-consuming and expensive. Furthermore, for tree-rings to robustly represent climate variability on longer timescales, the number of trees required greatly increases (Briffa and Melvin 2008) and production rates and costs can become a significant obstacle. Recently, reflected blue light from optically scanned images has been explored to investigate if this is a viable shortcut to robust warm season temperature reconstructions (e.g. McCarrol et al. 2002; Campbell et al. 2007). The parameter that that is measured is the minimum value of reflected blue light in every annual increment henceforth abbreviated (BLU). Previous studies have shown that BLU and MXD are highly correlated on annual to decadal scale. Now it is time to test BLU on multi-centennial scale.
Results and DiscussionResults and Discussion
Study AreaStudy Area
MethodsMethods
Figure 1. The fore fell Bårgå where dead and living trees were collected at the tree-line
Figure 5. MXD plotted against different chronology configurations of the BLU data. Notice the increased coherence with more complex BLU chronology configuration. This is not a sustainable way of producing BLU chronologies in future work beacuse there are also nuance differences between deadwood. A correction for nuance differences is needed to move forward with BLU on species that have heartwood/sapwood of this kind.
A new site in Northern Sweden 50 km north of the town of Arjeplog was sampled for Scots Pine (Pinus Sylvestris L.). Coordinates: Lat. 66° 17’ 37’’ N, Lon. 18° 14’ 59’’ E. The source area for the sampled trees was a north-facing slope on an 800 m high fore fell, Bårgå (Fig 1) where the pines form the tree-line at 700 m a.m.s.l.
For direct comparison of BLU vs. MXD, the same cores of wood were analyzed for both variables. The samples were prepared according to standard dendrochronological techniques (Schweingruber et al. 1978). Resins and extractives were chemically removed with ethanol in a Soxhlet extraction apparatus. The X-Ray was performed using an ITRAX multiscanner from Cox Analytical Systems (www.coxsys.se). The BLU was produced with a flatbed Scanner Epson Perfection V600 Series calibrated with SilverFast Ai professional scan software, standard protocol was followed according to Campbell et al. (2011). The raw MXD and BLU was standardized to remove age related trends in the series with Regional Curve Standardization (RCS; Briffa et al. 1992). This to enable comparison of chronologies on longer time scales than the mean age of the trees Cook et al. (1995). The BLU chronology was named BLUOriginal.
Figure 2. Top sample: living tree not alcohol refluxed, middle sample: living tree refluxed with alcohol for 24 h, bottom sample: dead tree refluxed in alcohol. Notice the nuance difference between the living and the dead refluxed trees.
Scots Pine has a pronounced difference in color between sapwood and heartwood (Fig 2). This color difference can not entirely be removed in extraction with alcohol. To account for this, a second BLU chronology was made which consisted one heartwood and one sapwood chronology, named BLUHeartwood/Sapwood. The sapwood chronology’s mean and variance was adjusted to fit the BLU heartwood chronology. A visual inspection of samples also revealed a distinct difference between heartwood from living and dead trees (Fig 2), and a third chronology was produced using similar division ans in the previous chronology and named BLUDeadwood/Heartwood/Sapwood. The mean and variance from the living tree heart wood chronology was adjusted to the dead tree heartwood chronology and finally the sap wood to the mean and variance of the combined “dead-living” composite chronology. During the overlap between the different chronologies the sample depth is varying, diminishing in the ends of each chronology hence replication weighted averages between the z-scored chronologies was made, see figure 3 for overlap.
First differenced MXD and BLU series have a correlation of r = 0.80 (n = 19 456) and the chronologies have a correlation of r = 0.95 (n = 810, Fig 4). Examining the common variability visually on longer timescales, the MXD and BLUOriginal covary excellently from 1200 A.D. to 1700 A.D. (Fig 5). After this there is a dramatic divergence. Examining the MXD and BLUHeartwood/Sapwood this divergence is reduced but there are still profound dissimilarities (Fig 5). Examining the MXD BLUDeadwood/Heartwood/Sapwood all centennial scale divergence is removed but the chronologies have a slight overall difference in trend (Fig 5).
ReferencesReferences
The BLU method is interpreted, from these results to be substantially more sensitive to the discoloration from waste products and resin in the heartwood and sapwood. Likely the longer waste products and resin reside in the wood, the more permanent and pronounced the discoloration becomes (Fig 2). One way of overcoming this vital weakness in BLU could be to quantify the background Blue reflectance caused by resin discoloration in the early wood of neighboring rings and, assumed that the latewood have the same background discoloration, remove this from BLU and make a new proxy. The difference in latewood and ambient early wood blue reflectance (δBLU) would enable samples with heavy discolorations to be used together with samples with little discoloration. And also ensure multi-centennial or even multi-millennial scale variability. If this drawback can be resolved it is clear that the value of BLU is tremendous since the climatic signal is equal in type, strength and field to MXD (Fig 6).
Since flatbed scanners, for example the one used in this study costs roughly thousand times less than the X-Ray machine used in this study, and the time of producing the BLU data was roughly half of the time of producing MXD data, the need for tweaking this proxy for optimum performance is of great value.
Figure 3. Expressed population signal, a measure of chronology confidence. EPS below 0.85 is considered to low for reconstructions. Sample depth through time where overlap of deadwood, living tree heartwood and sapwood is shown.
Figure 4. Scatter-plot with the relationship between first differenced MXD and BLU on series level in black and on chronology level in red.
Figure 6. Spatial correlations between MXD on left and BLU on rihgt with April-August Temperatures. The correlations were made on first differenced data. The star in each plot is the sampling site Bårgå, Arjeplog Sweden.
ConclusionConclusion
Briffa et al. (1992) Clim Dyn. 7:111-119; Briffa and Melvin (2011) In: Hughes M K, Diaz H F, Swetnam T W(ed), Dendroclimatology: Progress and Prospects, Springer Verlag, pp 378; Campbell et al. (2007) The Holocene 17:821; Campbell et al. (2011) Tree-ring Research 67:127-134; Cook et al. (1995) Holocene 5:229-237; McCarroll et al. (2002) Arctic, Antarctic and Alpine Research 34:450-453; Schweingruber et al. (1988) Boreas 17:559-566; Schweingruber et al. (1978) Tree-ring bull. 38:61-91
Acknowledgements This work was supported by Vetenskapsrådet and Formas (grants to Hans W Linderholm) The poster contributes to the Swedish strategic research area Biodiversity and Ecosystem services in a Changing Climate (BECC).
ReferencesReferences
