“dendRoAnalyst”: A tool for processing and analysing dendrometer data

Dendrometers are vital tools for studying the response of trees to intra-annual environmental changes in different temporal resolutions, ranging from hourly, daily to weekly time resolution. Dendrometers are increasingly used in forest management and tree physiological studies. Besides the data analysis, data processing is also challenging, time-consuming and potentially error-prone due to the immense number of measurements generated by self-registering electronic dendrometers. We present the package ‘dendRoAnalyst’ based on R statistical software to process and analyse dendrometer data using various approaches. This package offers algorithms for handling and pre-cleaning of dendrometer data before the application of subsequent data analytical steps. This includes identifying and erasing artefacts in dendrometer datasets not related to actual stem circumference change, identifying data gaps within records, and the possibility of change(s) in temporal resolution. Furthermore, the package can calculate different daily statistics of dendrometer data, including the daily amplitude of tree growth. The package dendRoAnalyst is therefore intended to facilitate researchers with a collection of functions for handling and analysing dendrometer data.     

Patterns of daily stem growth in different tree species in a warm-temperate forest in northern China

Radial growth in trees responds to environmental changes in various ways ranging from immediate to hysteretic responses. However, species-specific tree radial growth patterns and their responses to short-term weather changes are not fully understood. Here, the daily stem radial changes (SRCs) in four common tree species, linden (Tilia mongolica), birch (Betula dahurica), oak (Quercus wutaishanica) and larch (Larix principis-rupprechtii), were monitored with high-resolution point dendrometers during the main growing seasons in 2017–2019 on Dongling Mountain, northern China. The SRC was differentiated into tree water deficit-induced stem shrinkage (TWD) and growth-induced irreversible stem expansion (GRO) to evaluate species-specific responses to weather variables and short-term drought events. We found that the TWD and GRO of the four species were significantly different. The TWD was influenced primarily by the vapor pressure deficit (VPD), whereas the GRO was influenced primarily by precipitation (P). In linden and birch, a larger proportion of the GRO occurred at higher air temperature (T_mean) and VPD values; in contrast, the range of these changes was lower in oak and larch. With the increased durations of drought periods, oak and larch experienced large and rapid increases in TWD, whereas birch and linden showed small and slow increases. These results indicate that oak and larch would be sensitive to warmer and drier weather conditions predicted for the future, while linden and birch would have a conservative growth strategy. Our results provide further insights into the physiology of these four tree species and allow us to better predict the growth response of forest dynamics under climate change.     

广东黑石顶南亚热带常绿阔叶林树木生长研究(英文)

用测树器和年轮解析法 ,测定了广东黑石顶南亚热带常绿阔叶林的立木和幼树的径向生长和高生长。年轮解析法测得立木的年直径生长量在 0 .1～ 0 .5cm之间 ,一些立木的直径生长呈现出生长快的年份 ( 1～ 3a)和生长慢的年份 ( 1～ 3a)交替的节律。测树器测得立木 5a的年平均直径生长量为0 .0 74cm,5年期间测得有 1 7.6%的个体直径为零增长或负增长。立木的年高增长量为 1 0～ 50 cm,高生长高峰期通常在 1 0～ 30年龄。在树木生长的早期 ,高度的生长优于直径的生长 ,而在树木生长的中、后期 ,直径的生长逐渐优于高度的生长。用游标卡尺和卷尺测得幼树 (通常 1～ 3m高 )的直径和高度 5a的平均生长量分别为 0 .1 0 7cm和 4.76cm。 5a间没有幼树的直径生长为零增长或负增长 ,但约有 9%的个体的高度生长为零增长或负增长。     

Spatiotemporal alignment of radial tracheid diameter profiles of submontane Norway spruce

Studying intra-annual wood formation dynamics provides valuable information on how tree growth and forests are affected by environmental changes and climatic extreme events. This study has the aim to evaluate and to quantify synergetic potentials emerging from a combination of current state of the art techniques used to monitor intra-annual wood formation processes. Norway spruce trees were studied in detail during the growing season 2009 with weekly sampling of microcores, high resolution point-dendrometers and wood anatomical analysis. The combination of the applied techniques allowed us to convert the spatial scales of radial tracheid diameter profiles to seasonal time scales and to synchronize fluctuations in intra-annual cell diameter profiles. This spatiotemporal information was used to validate the recently introduced software MICA (Multiple interval-based curve alignment). In comparison to the conventional approach of averaging profiles of tree ring variables, the MICA aligned profiles exhibit a significantly higher synchronicity of the averaged data points. We also demonstrate two new features in the MICA application that enable to extrapolate spatiotemporal information between intra-annual profiles for the construction of robust mean (consensus) profiles that are representative for the population dynamics. By using a set of complementary techniques in an integrated approach, this study highlights a new methodological framework that can contribute to a better understanding of the environmental control of wood formation during the growing season.     

Differences in daily stem size variation and growth in two hybrid eucalypt clones

Understanding daily stem size variation is important as the net increment of a forest stand is ultimately determined by the accumulation of daily increment events. In this study, measurements of stem size at high spatial and temporal resolution were made using two commercial hybrid Eucalyptus clones [E. grandis × urophylla (GU) and E. grandis × camaldulensis (GC)] over a period of more than 3.5 years in order to better understand how daily stem growth is effected by variations in environmental conditions. It was evident that GU had fewer days on which net growth occurred than GC. However, when growth did occur, GU grew for longer each day and at a higher rate than GC. Thus, it still had an overall larger net stem increment during the study period. The GU clone had a markedly intermittent pattern of growth, such that growth essentially ceased under drought conditions, but responded rapidly when water became available. This confirms other findings that E. grandis × urophylla is more susceptible to drought stress than E. grandis × camaldulensis, but emphasizes that a strategy of “rapid response” when environmental conditions become temporarily non-limiting is a good one in terms of net increment at sites such as in this study.

Growth in stem diameter of Larix principis-rupprechtii and its response to meteorological factors in the south of Liupan Mountain, China

Research related to daily and seasonal pattern of stem growth of Larix principis-rupprechtii was carried out with the help of a dendrometer from June to September in 2005 in the Liupan Mountain, Ningxia, Northwestern China. The results indicated that daily fluctuation of stem diameter was rhythmic and it could be divided into three continuous phases: contraction, expansion and stem diameter growth when daily rainfall < 10 mm during the measurement period. Comparatively, it showed a different pattern compared with the former when daily rainfall ≥10 mm and in the subsequent days. Based on the work done by Deslauriers et al. a modified method was designed to calculate daily and cumulative stem growth, and it showed that seasonal pattern of cumulative stem growth was similar among five sample trees. From June and July, stem growth rate was quick and the values were in the range 27.0–44.2 μm per day. Relatively, they took on a slow growth rate from August to September, and the values were under 10 μm per day. And it also showed that there existed a significant difference in stem growth among sample trees, which could be as a result of the difference in tree domain and their positions in the stand. The relationship between daily stem growth and meteorological factors was studied by principle component analysis and partial correlation analysis, and the result indicated that the daily rainfall, daily minimum temperature, daily average solar radiation and vapor pressure deficit were four significant factors which determined the daily stem growth.     

A general model of intra‐annual tree growth using dendrometer bands

Tree growth is an important indicator of forest health, productivity, and demography. Knowing precisely how trees' grow within a year, instead of across years, can lead to a finer understanding of the mechanisms that drive these larger patterns. The growing use of dendrometer bands in research forests has only rarely been used to measure growth at resolutions finer than yearly, but intra‐annual growth patterns can be observed from dendrometer bands using precision digital calipers and weekly measurements. Here we present a workflow to help forest ecologists fit growth models to intra‐annual measurements using standard optimization functions provided by the R platform. We explain our protocol, test uncertainty in parameter estimates with respect to sample sizes, extend the optimization protocol to estimate robust lower and upper annual diameter bounds, and discuss potential challenges to optimal fits. We offer R code to implement this workflow. We found that starting values and initial optimization routines are critical to fitting the best functional forms. After using a bounded, broad search method, a more focused search algorithm obtained consistent results. To estimate starting and ending annual diameters, we combined the growth function with early and late estimates of beginning and ending growth. Once we fit the functions, we present extension algorithms that estimate periodic reductions in growth, total growth, and present a method of controlling for the shifting allocation to girth during the growth season. We demonstrate that with these extensions, an analysis of growth response to weather (e.g., the water available to a tree) can be derived in a way that is comparable across trees, years, and sites. Thus, this approach, when applied across broader data sets, offers a pathway to build inference about the effects of seasonal weather on growth, size‐ and light‐dependent patterns of growth, species‐specific patterns, and phenology.     

不同去趋势方法对基于Dendrometer数据的茎干水分动态分析的影响——以白扦为例

树木茎干半径变化记录仪(Dendrometer)监测的高精度数据不仅包括木质部的年内径向生长过程, 还包含由茎干水分的消耗和补充引起的可逆变化。然而, 不同的年内生长去趋势方法获得的茎干水分波动之间的差异性仍缺乏对比研究。基于芦芽山北坡针叶林下限白扦(Picea meyeri) 2015年生长季的茎干半径变化和环境因子的实时监测数据, 使用Gompertz生长模型(GPZ)、线性生长模型(LG)、零生长模型(ZG)、日值法(D)和茎干循环法(SC)模拟并去除茎干年内的生长趋势, 然后提取5种不同类型树木水分缺乏引起的茎干收缩(TWD_GPZ、TWD_LG、TWD_ZG、TWD_D和TWD_SC)以表征茎干水分亏缺, 并进一步对比分析了不同茎干水分亏缺序列对环境中水分状况的响应特征。研究发现: (1)不同去趋势方法计算的茎干水分亏缺的趋势和幅度有所差异, 可聚类为3组: TWD_LG和TWD_ZG、TWD_GPZ以及TWD_D和TWD_SC。同组或聚类距离接近的序列在生长季内每个月份都展现出显著的相关性。然而, TWD_LG、TWD_ZG和TWD_GPZ与TWD_D和TWD_SC在8月份相关性较弱。(2) TWD_D和TWD_SC与空气饱和水汽压差(VPD)的正相关关系比TWD_GPZ、TWD_LG和TWD_ZG更加稳定, 且具有更大的相关系数。5种茎干水分亏缺序列和土壤含水量(SWC)的关系在生长季内变化很大。(3)不同去趋势方法的茎干水分亏缺都随着水分胁迫程度(VPD/SWC)升高而显著增长。当胁迫程度较低时, TWD_SC对VPD/SWC的变化最为敏感(R² = 0.39, p < 0.001), 但是与TWD_ZG差别不大(R ² = 0.37, p < 0.001); 当胁迫程度较高时, TWD_ZG对VPD/SWC的敏感性最高(R ² = 0.59, p < 0.001)。综合对比来看, 零生长模型是比较适合研究区白扦生长季内茎干水分波动的去趋势方法, 其可为干旱胁迫条件下预测研究区树木的茎干水分动态及特征提供科学 依据。     

dendrometeR: Analyzing the pulse of trees in R

Dendrometers are measurement devices proven to be useful to analyze tree water relations and growth responses in relation to environmental variability. To analyze dendrometer data, two analytical methods prevail: (1) daily approaches that calculate or extract single values per day, and (2) stem-cycle approaches that separate high-resolution dendrometer records into distinct phases of contraction, expansion and stem-radius increment. Especially the stem-cycle approach requires complex algorithms to disentangle cyclic phases. Here, we present an R package, named dendrometeR, that facilitates the analysis of dendrometer data using both analytical methods. By making the package freely available, we make a first step towards comparable and reproducible methods to analyze dendrometer data. The package contains customizable functions to prepare, verify, process and plot dendrometer series, as well as functions that facilitate the analysis of dendrometer data (i.e. daily statistics or extracted phases) in relation to environmental data. The functionality of dendrometeR is illustrated in this note.     

A methodological framework to optimize models predicting critical dates of xylem phenology based on dendrometer data

Dendrometer measurements are a frequently used alternative to the laborious and time consuming microcoring to investigate intra-annual growth dynamics of trees. However, since dendrometer data not only comprise cambial growth, but also hydrological fluctuations, both signals need to be disentangled to derive critical dates of xylem phenology from dendrometer data. For this purpose, various approaches can be found in the literature, however a systematic comparison of the different options is still missing. In this study we present a methodological framework to evaluate the accuracy of different mathematical fittings to derive tree-ring phenology from dendrometer data and apply this approach to a data set comprised of three conifer species where high-resolution band dendrometer measurements and microcore sampling have been done in parallel. Based on our study we provide evidence that the most common approaches to derive onset and cessation of xylem cell enlargement from dendrometer data, i.e. applying absolute and relative thresholds to deterministic models fitted to dendrometer data, caused systematic deviations from the reference of xylogenesis observations, but could be improved by small adaptations. The most precise and unbiased predictions of xylem growth phenology were obtained by fitting the three-parameter Gompertz model to the dendrometer data and applying a relative threshold of 3.5% of annual increment to the model predictions for growth onset and an absolute threshold of 4.5 µm day^-1 based on the first model derivative for growth cessation. Our framework enables an improved usage of dendrometer data for the prediction of the onset and cessation of xylem cell enlargement, which are important ecological indicators to quantify the effects environmental changes on forest growth and the terrestrial carbon cycle.