Climate, soil nutrients, and stand characteristics jointly determine large-scale patterns of biomass growth rates and allocation in Pinus massoniana plantations

2022 ◽  
Vol 504 ◽  
pp. 119839
Author(s):  
Yanyan Ni ◽  
Zunji Jian ◽  
Lixiong Zeng ◽  
Jianfeng Liu ◽  
Lei Lei ◽  
...  
2019 ◽  
Vol 435 ◽  
pp. 120-127 ◽  
Author(s):  
Hao Zhang ◽  
Kelin Wang ◽  
Zhaoxia Zeng ◽  
Hu Du ◽  
Zhigang Zou ◽  
...  

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 475
Author(s):  
Lukáš Trávníček ◽  
Ivo Kuběna ◽  
Veronika Mazánová ◽  
Tomáš Vojtek ◽  
Jaroslav Polák ◽  
...  

In this work two approaches to the description of short fatigue crack growth rate under large-scale yielding condition were comprehensively tested: (i) plastic component of the J-integral and (ii) Polák model of crack propagation. The ability to predict residual fatigue life of bodies with short initial cracks was studied for stainless steels Sanicro 25 and 304L. Despite their coarse microstructure and very different cyclic stress–strain response, the employed continuum mechanics models were found to give satisfactory results. Finite element modeling was used to determine the J-integrals and to simulate the evolution of crack front shapes, which corresponded to the real cracks observed on the fracture surfaces of the specimens. Residual fatigue lives estimated by these models were in good agreement with the number of cycles to failure of individual test specimens strained at various total strain amplitudes. Moreover, the crack growth rates of both investigated materials fell onto the same curve that was previously obtained for other steels with different properties. Such a “master curve” was achieved using the plastic part of J-integral and it has the potential of being an advantageous tool to model the fatigue crack propagation under large-scale yielding regime without a need of any additional experimental data.


Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 404 ◽  
Author(s):  
Xin Huang ◽  
Chunbo Huang ◽  
Mingjun Teng ◽  
Zhixiang Zhou ◽  
Pengcheng Wang

Understanding the spatial variation of forest productivity and its driving factors on a large regional scale can help reveal the response mechanism of tree growth to climate change, and is an important prerequisite for efficient forest management and studying regional and global carbon cycles. Pinus massoniana Lamb. is a major planted tree species in southern China, playing an important role in the development of forestry due to its high economic and ecological benefits. Here, we establish a biomass database for P. massoniana, including stems, branches, leaves, roots, aboveground organs and total tree, by collecting the published literature, to increase our understanding of net primary productivity (NPP) geographical trends for each tree component and their influencing factors across the entire geographical distribution of the species in southern China. P. massoniana NPP ranges from 1.04 to 13.13 Mg·ha−1·year−1, with a mean value of 5.65 Mg·ha−1·year−1. The NPP of both tree components (i.e., stem, branch, leaf, root, aboveground organs, and total tree) show no clear relationships with longitude and elevation, but an inverse relationship with latitude (p < 0.01). Linear mixed-effects models (LMMs) are employed to analyze the effect of environmental factors and stand characteristics on P. massoniana NPP. LMM results reveal that the NPP of different tree components have different sensitivities to environmental and stand variables. Appropriate temperature and soil nutrients (particularly soil available phosphorus) are beneficial to biomass accumulation of this species. It is worth noting that the high temperature in July and August (HTWM) is a significant climate stressor across the species geographical distribution and is not restricted to marginal populations in the low latitude area. Temperature was a key environmental factor behind the inverse latitudinal trends of P. massoniana NPP, because it showed a higher sensitivity than other factors. In the context of climate warming and nitrogen (N) deposition, the inhibition effect caused by high temperatures and the lack or imbalance of soil nutrients, particularly soil phosphorus, should be paid more attention in the future. These findings advance our understanding about the factors influencing the productivity of each P. massoniana tree component across the full geographical distribution of the species, and are therefore valuable for forecasting climate-induced variation in forest productivity.


2020 ◽  
Vol 12 (12) ◽  
pp. 2056 ◽  
Author(s):  
Parinaz Rahimzadeh-Bajgiran ◽  
Chris Hennigar ◽  
Aaron Weiskittel ◽  
Sean Lamb

A fine-resolution region-wide map of forest site productivity is an essential need for effective large-scale forestry planning and management. In this study, we incorporated Sentinel-2 satellite data into an increment-based measure of forest productivity (biomass growth index (BGI)) derived from climate, lithology, soils, and topographic metrics to map improved BGI (iBGI) in parts of North American Acadian regions. Initially, several Sentinel-2 variables including nine single spectral bands and 12 spectral vegetation indices (SVIs) were used in combination with forest management variables to predict tree volume/ha and height using Random Forest. The results showed a 10–12 % increase in out of bag (OOB) r2 when Sentinel-2 variables were included in the prediction of both volume and height together with BGI. Later, selected Sentinel-2 variables were used for biomass growth prediction in Maine, USA and New Brunswick, Canada using data from 7738 provincial permanent sample plots. The Sentinel-2 red-edge position (S2REP) index was identified as the most important variable over others to have known influence on site productivity. While a slight improvement in the iBGI accuracy occurred compared to the base BGI model (~2%), substantial changes to coefficients of other variables were evident and some site variables became less important when S2REP was included.


2016 ◽  
Vol 73 (1) ◽  
pp. 125-139 ◽  
Author(s):  
Michael D. Yard ◽  
Josh Korman ◽  
Carl J. Walters ◽  
Theodore A. Kennedy

Rainbow trout (Oncorhynchus mykiss) have been purposely introduced in many regulated rivers, with inadvertent consequences on native fishes. We describe how trout growth rates and condition could be influencing trout population dynamics in a 130 km section of the Colorado River below Glen Canyon Dam based on a large-scale mark–recapture program where ∼8000 rainbow trout were recaptured over a 3-year period (2012–2014). There were strong temporal and spatial variations in growth in both length and weight as predicted from von Bertalanffy and bioenergetic models, respectively. There was more evidence for seasonal variation in the growth coefficient and annual variation in the asymptotic length. Bioenergetic models showed more variability for growth in weight across seasons and years than across reaches. These patterns were consistent with strong seasonal variation in invertebrate drift and effects of turbidity on foraging efficiency. Highest growth rates and relative condition occurred in downstream reaches with lower trout densities. Results indicate that reduction in rainbow trout abundance in Glen Canyon will likely increase trout size in the tailwater fishery and may reduce downstream dispersal into Grand Canyon.


2021 ◽  
Vol 244 ◽  
pp. 10020
Author(s):  
Tatiana Podolskaya ◽  
Maria Singkh

The risks and large-scale losses faced by the international community during the COVID-19 pandemic led to a recession in 2020. In these circumstances, of particular interest is the experience of China, which was able to maintain positive economic growth rates, demonstrating a unique resilience to modern challenges. The main objective of the study presented here is a statistical and structural analysis of the factors that ensure China’s international competitiveness and the resilience of its economy in the face of the COVID-19 pandemic. The analysis is expected to show which key factors of China’s international competitiveness have made its economy resilient to the challenges of the COVID-19 pandemic. The authors also hope to identify which promising developments, similar to China’s, will enhance the international competitiveness of the BRICS countries.


2021 ◽  
Vol 2 (4) ◽  
pp. 26-35
Author(s):  
Muhammad Ramzan ◽  

Basic soil composition, or more precisely, soil organic matter, soil clay mineralogy and soil texture have been in the core of most infrared spectroscopy research for soils. Of course, nutrient availability, soil structure, soil microbial activity and soil fertility have also been a major subject of interest over the past two decades. The determination of soil nutrients is now becoming a routine work at large scale to gain high yield. The large number of soil nutrients determining techniques are used. The current paper presented that among tested techniques, Near-infrared reflectance spectroscopy (NIRS) is a best technique which has been used widely with minimum time, low in cost, ecofriendly and rapid determination of chemical, physical properties and organic matter present in soil. Obviously, this useful technique can be used to estimate properties such as mineral composition, SOM, water, percentage of carbon, nitrogen and clay content. It could be used directly in soil mapping, for monitoring soil, for making inferences about its quality and function, and making geomorphological interpretations of its distribution. The development of most accurate and trustworthy NIRS approaches are required.


2021 ◽  
Vol 8 ◽  
Author(s):  
Joshua Himmelstein ◽  
Orencio Duran Vinent ◽  
Stijn Temmerman ◽  
Matthew L. Kirwan

The development and expansion of ponds within otherwise vegetated coastal marshes is a primary driver of marsh loss throughout the world. Previous studies propose that large ponds expand through a wind wave-driven positive feedback, where pond edge erosion rates increase with pond size, whereas biochemical processes control the formation and expansion of smaller ponds. However, it remains unclear which mechanisms dominate at a given scale, and thus how, and how fast, ponds increase their size. Here, we use historical photographs and field measurements in a rapidly submerging microtidal marsh to quantify pond development and identify the processes involved. We find that as small ponds emerge on the marsh platform, they quickly coalesce and merge, increasing the number of larger ponds. Pond expansion rates are maximized for intermediate size ponds and decrease for larger ponds, where the contribution of wave-driven erosion is negligible. Vegetation biomass, soil shear strength, and porewater biogeochemical indices of marsh health are higher in marshes adjacent to stable ponds than in those adjacent to unstable ponds, suggesting that pond growth rates are negatively related to the health of the surrounding marsh. We find that the model of Vinent et al. (2021) correctly predicts measured pond growth rates and size distribution, which suggest the different mechanisms driving pond growth are a result of marsh drowning due to sea level rise (SLR) and can be estimated by simplified physical models. Finally, we show that all relevant processes increasing pond size can be summarized by an empirical power-law equation for pond growth which predicts the temporal change of the maximum pond size as a lower bound for the total pond area in the system. This gives a timescale for the growth of ponds by merging and thus the critical time window for interventions to prevent the irreversible pond expansion associated with large scale pond merging.


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