Effects of cold conditions on the growth rates of a subtropical conifer

Scipioni, Marcelo Callegari; Fontana, Cláudia; Oliveira, J. M.; Santini, L.; Roig, Fidel A.; Tomazello-Filho, Mário

doi:10.1016/j.dendro.2021.125858

Cited by 7 publications

(5 citation statements)

References 30 publications

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“…However, there is no significant correlation between δ 18 O TR values and monthly temperature and RH (Figure 7). Extreme cold conditions can affect tree growth in the following year, but snowfall events in the study area occur during the non‐growing season, and the snow melts within 24 hr (Scipioni et al., 2021) and thus it has little effect on tree‐ring oxygen isotopes.…”

Section: Resultsmentioning

confidence: 99%

“…The lowest temperature was −14°C in June (winter) of 1952 and the highest was 27.5°C in January (summer) of 2018 (Epagri/Ciram, 2022). At the study site, frosts can occur from May to September, with a frequency of 10 days/year (Nimer, 1989), and snow events may occur in some years (Scipioni et al., 2021). With an annual mean RH of 85% and a range of 78%–92% (Figure 1b), the climate can be classified as humid subtropical oceanic with a temperate summer, based on Köppen's classification (Alvares et al., 2013).…”

Section: Methodsmentioning

confidence: 99%

“…in the southern and southeastern Brazilian mountains. A. angustifolia forms growth rings with an anatomical boundary marked by dark cells and dense latewood at the end of the growth year (Oliveira et al, 2010;Scipioni et al, 2021), and it has been used for tree-ring studies over the subtropics (Panarello & Dapeña, 2009;Prestes et al, 2018;Seitz & Kanninen, 1989).…”

Section: Sampling Site and Study Speciesmentioning

confidence: 99%

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Monthly Precipitation Reconstruction in Subtropical South America Using Seasonal Tree‐Ring Oxygen Isotopes

Liu,

Xu,

Fontana

et al. 2023

JGR Biogeosciences

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The South American Summer Monsoon (SASM) is one of the most important climate systems in the tropical and subtropical regions of South America, and transports Atlantic moisture to the South American continent. However, there are few high‐resolution tree ring based studies of the SASM due to the difficulty of crossdating and the lack of dependable moisture proxies based on tree‐ring width. In this study, we use intra‐annual tree‐ring oxygen isotope (δ18OTR) data (E.V.A 03w, E.V.Ar11e, E.V.Ar12e; the full name of sample code is Erval Velho ‐ Araucaria) for crossdating, and to extract climate signals and reconstruct monthly precipitation. Our data are from Araucaria angustifolia in southern Brazil, and each annual tree‐ring comprises four parts (parts 1, 2, 3, 4) during 1960–2016. The intra‐annual δ18OTR data show pronounced seasonal variations with a decreasing trend in the growing season. The intra‐annual δ18OTR data record variations in precipitation δ18O values, and the interannual δ18OTR data record a precipitation amount. The δ18OTR values of parts 1 and 2 of each ring show the strongest correlation with precipitation at the beginning of the SASM (i.e., December). δ18OTR values of Part 3 have the strongest correlation with precipitation during January–February, and those of Part 4 are strongly correlated with precipitation during February–June. The seasonal δ18OTR values can be used to reconstruct monthly precipitation in the growing season. Spatial correlations between monthly precipitation reconstruction and global sea surface temperatures reveal that EI Niño‐Southern Oscillation (ENSO) regulate seasonal precipitation and affect the δ18OTR values in southern Brazil.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Sampling Site and Study Speciesmentioning

confidence: 99%

See 1 more Smart Citation

Monthly Precipitation Reconstruction in Subtropical South America Using Seasonal Tree‐Ring Oxygen Isotopes

Liu,

Xu,

Fontana

et al. 2023

JGR Biogeosciences

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“…Variations in temperature, precipitation and solar radiation, among other meteorological elements, are more significant in areas of temperate climate than in tropical, when discussing the growth rate of the trees [43]. The relationship between meteorological variables and the exchange activity of Araucaria angustifolia trees has been observed by several authors [4,6,8,44,45], through growth rings that present a seasonal rhythm. However, the exchange activity of Araucaria angustifolia presents a difference between the sample sites regarding the periods of initial and latewood formation.…”

Section: Resultsmentioning

confidence: 99%

Climate Influence in Dendrochronological Series of Araucaria angustifolia from Campos do Jordão, Brazil

et al. 2021

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A dendrochronological series of Araucaria angustifolia was analyzed for a better understanding of the climatic factors that operate in Campos do Jordão city, São Paulo state, Brazil. The dendroclimatic analysis was carried out using 45 samples from 16 Araucaria angustifolia trees to reconstruct the precipitation and the temperature over the 1803–2012 yearly interval. To this end, Pearson’s correlation was calculated between mean chronology and the climatic time series using a monthly temporal resolution to calibrate our models. We obtained correlations as high as r=0.22(α=0.1) for precipitation (February), and r=0.21(α=0.1) for temperature (March), both corresponding to the end of the summer season. Our results show evidence of temporal instabilities because the correlations for the halves of 1963–2012 were very different, as well as for the full period. To overcome this problem, the dendrochronological series and the climatic data were investigated using the wavelet techniques searching for time-dependent cause–effect relationships. From these analyses, we find a strong influence of the region’s precipitation and temperature on the growth of tree ring widths.

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“…Forests provide essential ecosystem services and goods for people and nature, including biodiversity conservation, climate change mitigation, water conservation, food and energy, timber, and other raw materials for forest-based industries and bioeconomic value chains. [1][2][3][4] Despite numerous advances in forestry breeding technologies to guide the breeding process of forest tree seedlings, it is still very difficult to achieve effective forestry monitoring of growth condition, irrigation, and fertilization, microenvironmental changes, and pest and disease control of forest tree seedlings. [5,6] The representative application examples are discussed and the possibility of practical application in intelligent forestry is analyzed.…”

Section: Introductionmentioning

confidence: 99%

Plant‐Wearable Sensors for Intelligent Forestry Monitoring

Han

et al. 2022

Advanced Sustainable Systems

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Traditional monitoring technologies, such as infrared thermography, [7] hyperspectral techniques, [8] wireless sensor networks, [9] satellite imaging and remote sensing techniques, [10] etc. have limited their use in monitoring the growth of forest seedlings due to their high cost, difficult installation, complicated signal conversion, and difficulty in achieving high temporal resolution for real-time monitoring. [11] Moreover, the operational complexity, nonportability, and poor biocompatibility of traditional rigid sensors used for forestry monitoring hinder the healthy growth of seedlings dealing with developing and fragile tree seedlings. [12,13] On the other hand, the growth and development of seedlings directly affect the quality of forestry trees and changes in the forest ecological environment. [14] Plant physiological metabolism, plant growth in seedling cultivation and growing environment monitoring of young trees need to be monitored to evaluate plant growth characteristics, and then integrated with molecular theories such as genetic modification in forest genetics and breeding. [15,16] In this process, plant-wearable sensors play a very important role, and the lack of intelligent forestry monitoring technology brings problems such as high cost, long time, and inaccurate data. Hence, it is essential to develop intelligent strategies that monitor the growth of young forests and the harmful stresses during the growth of young forests, which induces unique requirement of flexible plant-wearable sensors for forestry monitoring.Meanwhile, plant-wearable sensors can be closely fitted to the surface of tree seedlings for real-time continuous monitoring without causing damage to the seedlings themselves by using their own characteristics such as flexibility and stretchability, [17,18] thus appealing to this wearables requirement for intelligent forestry monitoring. Therefore, flexible, lightweight, and wearable properties of plant-wearable sensors are urgently needed for this application of intelligent forestry monitoring.Herein, this paper introduces the recent development status of plant-wearable sensors in detail from the perspective of early intelligent monitoring in forestry and enumerates their structural compositions and working mechanisms. Application scenarios of plant wearables, including for the detection of plant physiological metabolism and plant growth, signal molecule detection, forest fire prevention, growth environment monitoring, and development of self-powered wireless monitoring system, are systematically summarized (Figure 1). Flexible plant-wearable sensors show great potential for precise and intelligent monitoring of real-time physical and chemical signals in forestry seedlings to optimize their growth environment, increase carbon sequestration, and promote underforest ecosystems. Furthermore, plant-wearable sensors can help prevent threats such as forest ecological deterioration, forest diseases, and insect pests. Herein, recent advances in emerging plantwearable sensors used in forest...

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Effects of cold conditions on the growth rates of a subtropical conifer

Cited by 7 publications

References 30 publications

Monthly Precipitation Reconstruction in Subtropical South America Using Seasonal Tree‐Ring Oxygen Isotopes

Monthly Precipitation Reconstruction in Subtropical South America Using Seasonal Tree‐Ring Oxygen Isotopes

Climate Influence in Dendrochronological Series of Araucaria angustifolia from Campos do Jordão, Brazil

Plant‐Wearable Sensors for Intelligent Forestry Monitoring

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