Abstract
We congratulate the authors on an important contribution to temperature reconstruction methodology applicable to pollen data. Pollen data is more challenging to model than other climate proxies, such as measurements on tree rings, because of the categorical nature of pollen assemblage data and the dating uncertainty inherent to any sedimentary proxy. The authors are commended on developing a reconstruction methodology that incorporates Bchron and Bummer. In this discussion, we discuss several ideas prompted by our reading of this interesting and novel paper.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 428-430 |
| Number of pages | 3 |
| Journal | Environmetrics |
| Volume | 27 |
| Issue number | 7 |
| DOIs |
|
| State | Published - Nov 1 2016 |
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Keywords
- memory length
- spatial correlation
- temperature change
ASJC Scopus subject areas
- Statistics and Probability
- Ecological Modeling
Cite this
Discussion on temperature reconstruction with sediment core data in Ilvonen et al. / Li, Bo; Barboza, Luis; Tingley, Martin; Viens, Frederi.
In: Environmetrics, Vol. 27, No. 7, 01.11.2016, p. 428-430.Research output: Contribution to journal › Comment/debate
}
TY - JOUR
T1 - Discussion on temperature reconstruction with sediment core data in Ilvonen et al.
AU - Li, Bo
AU - Barboza, Luis
AU - Tingley, Martin
AU - Viens, Frederi
PY - 2016/11/1
Y1 - 2016/11/1
N2 - We congratulate the authors on an important contribution to temperature reconstruction methodology applicable to pollen data. Pollen data is more challenging to model than other climate proxies, such as measurements on tree rings, because of the categorical nature of pollen assemblage data and the dating uncertainty inherent to any sedimentary proxy. The authors are commended on developing a reconstruction methodology that incorporates Bchron and Bummer. In this discussion, we discuss several ideas prompted by our reading of this interesting and novel paper.
AB - We congratulate the authors on an important contribution to temperature reconstruction methodology applicable to pollen data. Pollen data is more challenging to model than other climate proxies, such as measurements on tree rings, because of the categorical nature of pollen assemblage data and the dating uncertainty inherent to any sedimentary proxy. The authors are commended on developing a reconstruction methodology that incorporates Bchron and Bummer. In this discussion, we discuss several ideas prompted by our reading of this interesting and novel paper.
KW - memory length
KW - spatial correlation
KW - temperature change
UR - http://www.scopus.com/inward/record.url?scp=84989847029&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84989847029&partnerID=8YFLogxK
U2 - 10.1002/env.2399
DO - 10.1002/env.2399
M3 - Comment/debate
AN - SCOPUS:84989847029
VL - 27
SP - 428
EP - 430
JO - Environmetrics
JF - Environmetrics
SN - 1180-4009
IS - 7
ER -