Insights into the BRT (Boosted Regression Trees) Method in the Study of the Climate-Growth Relationship of Masson Pine in Subtropical China

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.

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Assimilation of Pseudo-Tree-Ring-Width observations into an Atmospheric General Circulation Model

10.5194/cp-2016-92 ◽

2016 ◽

Cited By ~ 1

Author(s):

Walter Acevedo ◽

Bijan Fallah ◽

Sebastian Reich ◽

Ulrich Cubasch

Keyword(s):

Tree Ring ◽

Tree Growth ◽

General Circulation ◽

Climate Model ◽

Global Climate Model ◽

Ring Width ◽

Circulation Model ◽

Forward Model ◽

Limiting Factors ◽

Tree Ring Width

Abstract. We investigate the assimilation of Tree-Ring-Width (TRW) chronologies into an atmospheric global climate model using Ensemble Kalman Filter (EnKF) techniques and a process-based tree-growth forward model as observation operator. Our results, within a perfect-model experiment setting, indicate that the non-linear response of tree-growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged (EnKF) methodology. Moreover, this skill loss appeared significantly sensitive to the structure of growth rate function, used to represent the Principle of Limiting Factors (PLF)s within the forward model. On the other hand, it was observed that the error reduction achieved by assimilating a particular pseudo-TRW chronology is modulated by the strength of the yearly internal variability of the model at the chronology site. This result might help the dendrochronology community to optimize their sampling efforts. In our experiments, the ''online'' (with cycling) paleao Data Assimilation (DA) approach did not outperform the ''offline'' (no-cycling) one, despite its considerable additional implementation complexity.

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Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

Climate of the Past ◽

10.5194/cp-13-545-2017 ◽

2017 ◽

Vol 13 (5) ◽

pp. 545-557 ◽

Cited By ~ 9

Author(s):

Walter Acevedo ◽

Bijan Fallah ◽

Sebastian Reich ◽

Ulrich Cubasch

Keyword(s):

Tree Ring ◽

Tree Growth ◽

General Circulation ◽

Climate Model ◽

Global Climate Model ◽

Ring Width ◽

Circulation Model ◽

Forward Model ◽

Limiting Factors ◽

Tree Ring Width

Abstract. Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

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Nonlinear responses of white spruce growth to climate variability in interior Alaska

Canadian Journal of Forest Research ◽

10.1139/cjfr-2012-0372 ◽

2013 ◽

Vol 43 (4) ◽

pp. 331-343 ◽

Cited By ~ 35

Author(s):

Andrea H. Lloyd ◽

Paul A. Duffy ◽

Daniel H. Mann

Keyword(s):

Picea Glauca ◽

Boreal Forests ◽

General Circulation ◽

Circulation Model ◽

White Spruce ◽

Climatic Conditions ◽

Boosted Regression Trees ◽

Temperature And Precipitation ◽

Interior Alaska ◽

And Function

Ongoing warming at high latitudes is expected to lead to large changes in the structure and function of boreal forests. Our objective in this research is to determine the climatic controls over the growth of white spruce (Picea glauca (Moench) Voss) at the warmest driest margins of its range in interior Alaska. We then use those relationships to determine the climate variables most likely to limit future growth. We collected tree cores from white spruce trees growing on steep, south-facing river bluffs at five sites in interior Alaska, and analyzed the relationship between ring widths and climate using boosted regression trees. Precipitation and temperature of the previous growing season are important controls over growth at most sites: trees grow best in the coolest, wettest years. We identify clear thresholds in growth response to a number of variables, including both temperature and precipitation variables. General circulation model (GCM) projections of future climate in this region suggest that optimum climatic conditions for white spruce growth will become increasingly rare in the future. This is likely to cause short-term declines in productivity and, over the longer term, probably lead to a contraction of white spruce to the cooler, moister parts of its range in Alaska.

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Does acclimation of plant traits improve dynamic vegetation modelling of a tree species?

10.5194/egusphere-egu2020-19768 ◽

2020 ◽

Author(s):

Louis François ◽

Alain Hambuckers ◽

Alexandra-Jane Henrot ◽

Franck Trolliet ◽

Jean-Luc Pitance ◽

...

Keyword(s):

General Circulation ◽

Circulation Model ◽

Climate Projections ◽

Regression Equations ◽

Climate Factors ◽

Vegetation Model ◽

Dynamic Vegetation Model ◽

Vegetation Modelling ◽

Atlas Mountains ◽

Middle Atlas

<p>Dynamic vegetation modelling is intensively used with plant functional types which limits the range of interest of obtained outputs for other fields of knowledge like conservation science. An alternative approach is to simulate plant species. This however requires additional data, i.e. morphological and physiological traits values characterizing the species and determining their functional properties. However, not only many traits vary among the species belonging to the same plant functional type but also the traits vary broadly according to climate factors.</p><p>Since most of the traits are functional, their values may be critical for dynamic vegetation model outputs. We measured several traits (specific leaf area, leaf and sapwood C:N) of Cedrus atlantica in its native range, the Rif and Middle Atlas Mountains of Morocco, as well as in some plantations in western Europe. Trait values exhibit significant variations between the sampled sites. It is possible to predict these trait values using multiple regression with climate factors as explanatory variables. Using regression equations, we produced spatial- and time-varying traits over the study area. We implemented these equations in the CARAIB dynamic vegetation model and tested whether they improve the simulation of C. atlantica in the Rif and Middle Atlas Mountains, by comparing the net primary productivities and biomasses computed with and without trait variation, with those retrieved from measurements on the sampled sites. We then performed simulations of the future using climate projections of the regional climate model RCA4 nested in HadGEM2 general circulation model under the RCP8.5 scenario, in order to test the influence of trait acclimation on the predicted future changes in the range and productivity of the species.</p>

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General Circulation Model Development

10.1016/s0074-6142(00)x8046-1 ◽

2000 ◽

Keyword(s):

General Circulation Model ◽

General Circulation ◽

Model Development ◽

Circulation Model

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Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square

Xplore Journal of Statistics ◽

10.29244/xplore.v8i1.275 ◽

2019 ◽

Vol 8 (1) ◽

Author(s):

Khairunnisa Khairunnisa ◽

Rizka Pitri ◽

Victor P Butar-Butar ◽

Agus M Soleh

Keyword(s):

Statistical Downscaling ◽

General Circulation ◽

Principal Component Regression ◽

Circulation Model ◽

Principal Component ◽

Meteorological Station ◽

Grid Size ◽

Partial Least Square ◽

Least Square ◽

Output Data

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.

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Predicting the future distribution of Polar Bear Habitat in the polar basin from resource selection functions applied to 21st century general circulation model projections of sea ice

10.3133/70174076 ◽

2007 ◽

pp. 1-55 ◽

Cited By ~ 7

Author(s):

George M. Durner ◽

David Douglas ◽

Ryan M. Nielson ◽

Steven C. Amstrup ◽

Trent L. McDonald

Keyword(s):

Sea Ice ◽

General Circulation Model ◽

21St Century ◽

Resource Selection ◽

General Circulation ◽

Polar Bear ◽

Circulation Model ◽

Resource Selection Functions ◽

The Future

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On the impact of sea ice in a global ocean circulation model

Annals of Glaciology ◽

10.3189/s0260305500013884 ◽

1997 ◽

Vol 25 ◽

pp. 111-115 ◽

Cited By ~ 3

Author(s):

Achim Stössel

Keyword(s):

Southern Ocean ◽

Sea Ice ◽

Ocean Circulation ◽

General Circulation ◽

Thermohaline Circulation ◽

Circulation Model ◽

Deep Ocean ◽

Global Ocean ◽

Convective Activity ◽

The Impact

This paper investigates the long-term impact of sea ice on global climate using a global sea-ice–ocean general circulation model (OGCM). The sea-ice component involves state-of-the-art dynamics; the ocean component consists of a 3.5° × 3.5° × 11 layer primitive-equation model. Depending on the physical description of sea ice, significant changes are detected in the convective activity, in the hydrographic properties and in the thermohaline circulation of the ocean model. Most of these changes originate in the Southern Ocean, emphasizing the crucial role of sea ice in this marginally stably stratified region of the world's oceans. Specifically, if the effect of brine release is neglected, the deep layers of the Southern Ocean warm up considerably; this is associated with a weakening of the Southern Hemisphere overturning cell. The removal of the commonly used “salinity enhancement” leads to a similar effect. The deep-ocean salinity is almost unaffected in both experiments. Introducing explicit new-ice thickness growth in partially ice-covered gridcells leads to a substantial increase in convective activity, especially in the Southern Ocean, with a concomitant significant cooling and salinification of the deep ocean. Possible mechanisms for the resulting interactions between sea-ice processes and deep-ocean characteristics are suggested.

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