How to improve dating quality and reduce noise in tree-ring based debris-flow reconstructions

Tree rings have been used to reconstruct the occurrence of debris flows and other mass movements. Identification of past activity was typically based on the presence of growth anomalies in trees, with a focus on scars, stem tilting, trunk burial or apex decapitation. Clear guidelines have been missing so far and the dating of events has only rarely been based on thresholds so as to distinguish signal from noise. In a similar way, the spatial distribution of affected trees has not normally been considered in mass movement reconstructions, and was at best used as a subjective exclusion factor. This study therefore aims at improving dating quality of and reducing noise in debris-flow time series. Based on a dataset of 803 increment cores (385 trees) affected by debris flows, we reconstruct event histories using (i) a classical experts' approach, (ii) a weighted index (W_it) of responding trees as well as (iii) Moran's I and Getis–Ord Local Gi indices. We identify similarities and differences in results and then investigate subsets of the tree-ring sample to define ideal sampling positions on debris-flow cones and guidelines for sample depth.     

Sub-footprint analysis to uncover tree height variation using ICESat/GLAS

Detailed forest height data are an indispensable prerequisite for many forestry and earth science applications. Existing research of using Geoscience Laser Altimeter System (GLAS) data mainly focuses on deriving average or maximum tree heights within a GLAS footprint, i.e. an ellipse with a diameter of 65 m. However, in most forests, it is likely that the tree heights within such ellipse are heterogeneous. Therefore, it is desired to uncover detailed tree height variation within a GLAS footprint. To the best of our knowledge, no such methods have been reported as of now. In this study, we aim to characterize tree heights’ variation within a GLAS footprint as different layers, each of which corresponds to trees with similar heights. As such, we developed a new method that embraces two steps: first, a refined Levenberg–Marquardt (LM) algorithm is proposed to decompose raw GLAS waveform into multiple Gaussian signals, within which it is hypothesized that each vegetation signal corresponds to a particular tree height layer. Second, for each layer, three parameters were first defined: Canopy Top Height (CTH), Crown Length (CL), and Cover Proportion (CP). Then we extracted the three parameters from each Gaussian signal through a defined model. In order to test our developed method, we set up a study site in Ejina, China where the dominant specie is Populus euphratica. Both simulated and field tree height data were adopted. With regard to the simulation data, results presented a very high agreement for the three predefined parameters between our results and simulation data. When our methods were applied to the field data, the respective R² become 0.78 (CTH), CL (R² = 0.76), CP (R² = 0.74). Overall, our studies revealed that large footprint GLAS waveform data have the potentials for obtaining detailed forest height variation.     

Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST)

Land cover changes associated with urbanisation modify microclimate, leading to urban heat islands, whereby cities are warmer than the surrounding countryside. Understanding the factors causing this phenomenon could help urban areas adapt to climate change and improve living conditions of inhabitants. In this study, land surface temperatures (LST) of Aarhus, a city in the high latitudes, are estimated from the reflectance of a thermal band (TIRS1; Band 10; 10.60–11.19 μm) of Landsat 8 on five dates in the summer months (one in 2015, and four in 2018). Spectral indices, modelled on the normalised difference vegetation index (NDVI), using all combinations of the first seven bands of Landsat 8 are calculated and their relationships with LST, analysed. Land cover characteristics, in terms of the percentages of tree cover, building cover and overall vegetation cover are estimated from airborne LiDAR data, building footprints and 4-band aerial imagery, respectively. The correlations between LST, the spectral indices and land cover are estimated.The difference in mean temperature between the rural and urban parts of Aarhus is up to 3.96 °C, while the difference between the warmer and colder zones (based on the mean and SD of LST) is up to 13.26 °C. The spectral index using the near infrared band (NIR; Band 5; 0.85-0.88 μm) and a short-wave infrared band (SWIR2; Band 7; 2.11–2.29 μm) has the strongest correlations (r: 0.62 to 0.89) with LST for the whole study area. This index is the inverse of normalised burn ratio (NBR), which has been used for mapping burnt areas. Spectral indices using different combinations of the infrared bands have stronger correlations with LST than the more widely used vegetation indices such as NDVI. The percentage of tree cover has a higher negative correlation (Pearson’s r: -0.68 to -0.75) with LST than overall vegetation cover (r: -0.45 to -0.63). Tree cover and building cover (r: 0.53 to 0.71) together explain up to 68 % of the variation in LST. Modification of tree and building cover may therefore have the potential to regulate urban LST.     

Assessing the sensitivity of site index models developed using bi-temporal airborne laser scanning data to different top height estimates and grid cell sizes

Site productivity and forest growth are critical inputs into projecting wood volume and biomass accumulation over time. Site productivity, which is determined most commonly using site index models is also the primary criterion to consider many forest management decisions. Most of the previous research utilizing the remote sensing data for assessment of site index with forest height are based on the existing site index models developed with traditional dendrometric methods. However, these traditional methods are both time-consuming and expensive. This study demonstrates how bi-temporal airborne laser scanning (ALS) data collected within the 8-year period can be used for the development of site index models for Scots pine. The accuracy of ALS-derived models was assessed by comparison to the reference site index model developed based on data from stem analysis of 174 felled Scots pine trees. We evaluated the effect of different height metrics and grid cell size on the trajectory of site index models developed from ALS-derived measurements. Four methods of estimating top height from ALS point clouds were evaluated: 95th, 99th and 100th percentiles of point clouds and an individual tree detection approach (ITD). The models were created for a range of grid cell sizes: 10 × 10 m, 30 × 30 m, and 50 × 50 m. The results indicate that bitemporal ALS data could substitute traditional methods that have been applied to date for stand growth modelling. It was found that top height increment can be estimated by using both ITD approach and the 100th percentile of point cloud giving an appropriate top height (TH) increment estimation. Observed growth curves of reference trees agreed best with the trajectories that were obtained based on TH calculated using ITD method (R² = 0.892) and 100th percentile (R² = 0.797). In case of TH obtained from 99th and 95th percentiles only weak correlation was found: R² = 0.358 and R² = 0.213, accordingly. The height growth models developed with 95th and 99th percentiles of point cloud were not compatible with the reference model. We also found that grid cell size did not affect the model height growth trajectories. Irrespective of the grid cell size, the obtained model trajectories for the given method of TH estimation are nearly identical for cells 10 × 10, 30 × 30 and 50 × 50 m.     

Exploring full-waveform LiDAR parameters for tree species classification

Precise tree species classification with high density full-waveform LiDAR data is a key research topic for automated forest inventory. Most approaches constrain to geometric features and only a few consider intensity values. Since full-waveform data offers a much larger amount of deducible information this study explores a high number of parameter and feature combinations. Those variables having the highest impact on species differentiation are determined. To handle the large amount of airborne full-waveform data and to extract a comprehensive number of variable combinations an improved algorithm was developed. The full-waveform point parameters amplitude, width, range corrected intensity and total number of targets within a beam are transferred into raster covering a test site of 10 km². It was possible to isolate the three most important variables based on the intensity, the width and the total number of targets. Up to six tree species were classified with an overall accuracy of 57%, limiting to the four main species accuracy was improved to 78% and constraining just to conifers and broadleaved trees even 91% could be classified correctly.     

Scaling smallholder tree cover restoration across the tropics

Restoring tree cover in tropical countries has the potential to benefit millions of smallholders through improvements in income and environmental services. However, despite their dominant landholding shares in many countries, smallholders’ role in restoration has not been addressed in prior global or pan-tropical restoration studies. We fill this lacuna by using global spatial data on trees and people, national indicators of enabling conditions, and micro-level expert information. We find that by 2050, low-cost restoration is feasible within 280, 200, and 60 million hectares of tropical croplands, pasturelands, and degraded forestlands, respectively. Such restoration could affect 210 million people in croplands, 59 million people in pasturelands and 22 million people in degraded forestlands. This predominance of low-cost restoration opportunity in populated agricultural lands has not been revealed by prior analyses of tree cover restoration potential. In countries with low-cost tropical restoration potential, smallholdings comprise a significant proportion of agricultural lands in Asia (∼76 %) and Africa (∼60 %) but not the Americas (∼3%). Thus, while the Americas account for approximately half of 21st century tropical deforestation, smallholder-based reforestation may play a larger role in efforts to reverse recent forest loss in Asia and Africa than in the Americas. Furthermore, our analyses show that countries with low-cost restoration potential largely lack policy commitments or smallholder supportive institutional and market conditions. Discussions among practitioners and researchers suggest that four principles – partnering with farmers and prioritizing their preferences, reducing uncertainty, strengthening markets, and mobilizing innovative financing – can help scale smallholder-driven restoration in the face of these challenges.     

我国晚中生代单缝孢真蕨植物兴衰史及意义

从大化石和孢粉资料两方面总结了我国晚中生代单缝孢类真蕨植物的特点及其兴衰史，认为单缝孢类真蕨植物的在我国北方地区早白垩世植物群中的出现，繁盛和衰退与该地区的潮湿，特别是温暖潮湿型古气候背景关系十分密切，据此阐明了该类植物的潮湿，特别是温暖潮湿型古气候的指示意义，其中多数化石与现生真蕨Ａｔｈｙｒｉｕｍ，Ｄｒｙｏｐｔｅｒｉｓ属等的形态和繁殖器官结构非常相拟，反映真蕨类进入了一个新的演化阶段，并提出Ｄｒ     

Search for Solar Periodicities in Tree-ring Widths from Concórdia (S.C., Brazil)

Tree ring studies are usually used to determine or verify climatic factors prevailing at a given place or region that may cause tree-ring width variations. Few studies are dedicated to the solar phenomena which may underlie these tree-ring width variations. Furthermore, it is known that some terrestrial phenomena are influenced by short- and long-time scale solar variability. An optical and computational method was set up and applied to tree samples (Araucaria angustifolia from Santa Catarina State in Southern Brazil) in order to obtain a growth ring width mean chronology. Spectral analysis is used for the search of periodicities, by maximum entropy and iterative regression methods. The results evidenced several embedded signals at periods which may be related to solar activity variations. Cross-correlation analysis between sunspot number and tree-ring data was performed and a lag of zero year was obtained. From our work, it seems that the tropical conifer species Araucaria angustifolia may be a good choice for studies on Sun-Earth relationships and their regional effects.     

近1100年来柴达木盆地干湿气候演变特征及趋势预测

利用柴达木盆地东北缘宗务隆山和沙利克山采集的祁连圆柏年轮宽度序列及其与降水变化的响应关系，重建了柴达木盆地近1100年来的降水序列，分析了1100年间的旱涝演变特征，并对未来演变趋势进行了预测。研究表明：采用祁连圆柏年轮宽度序列EOF分析的第一主分量与德令哈降水序列的关系，重建了降水变化方程，恢复了柴达木盆地历史降水序列；过去1100年以来柴达木盆地经历了4个相对湿润和4个相对干旱的阶段，最近的1971—2000年是近千年来相对多雨的阶段，但20世纪90年代以来呈现出减少趋势，同时降水序列存在着准3年的最显著性周期；推测未来50年柴达木盆地的降水可能以偏少为主。     

Paleoclimate histories improve access and sustainability in index insurance programs

Proxy-based climate reconstructions can extend instrumental records by hundreds of years, providing a wealth of climate information at high temporal resolution. To date, however, their usefulness for informing climate risk and variability in policy and social applications has been understudied. Here, we apply tree-ring based reconstructions of drought for the last 700 years in a climate index insurance framework to show that additional information from long climate reconstructions significantly improves our understanding of the underlying climate distributions and variability. We further show that this added information can be used to better characterize risk to insurance providers, in many cases providing meaningful reductions in long-term contract costs to farmers in stand-alone policies. The impact of uncertainty on insurance premiums can also be reduced when insurers diversify portfolios, and the availability of long-term climate information from tree rings across a broad geographic range provides an opportunity to characterize spatial correlation in climate risk across geographic regions. Our results are robust to the range of climate variability experienced over the last 400 years and in model simulations of the twenty-first century, even within the context of changing baselines due to low frequency variability and secular climate trends. These results demonstrate the utility of longer-term climate histories in index insurance applications. Furthermore, they make the case from a climate-variability perspective for the continued importance of such approaches to improving the instrumental climate record, even into a non-stationary climate future.