Forest Age Drives the Resource Utilization Indicators of Trees in Planted and Natural Forests in China.

Specific leaf area (SLA) and leaf dry matter content (LDMC) are key leaf functional traits commonly used to reflect tree resource utilization strategies and predict forest ecosystem responses to environmental changes. Previous research on tree resource utilization strategies (SLA and LDMC) primarily focused on the species level within limited spatial scales, making it crucial to quantify the spatial variability and driving factors of these strategies. Whether there are discrepancies in resource utilization strategies between trees in planted and natural forests, and the dominant factors and mechanisms influencing them, remain unclear. This study, based on field surveys and the literature from 2008 to 2020 covering 263 planted and 434 natural forests in China, using generalized additive models (GAMs) and structural equation models (SEMs), analyzes the spatial differences and dominant factors in tree resource utilization strategies between planted and natural forests. The results show that the SLA of planted forests is significantly higher than that of natural forests (p < 0.01), and LDMC is significantly lower (p < 0.0001), indicating a "faster investment-return" resource utilization strategy. As the mean annual high temperature (MAHT) and mean annual precipitation (MAP) steadily rise, trees have adapted their resource utilization strategies, transitioning from a "conservative" survival tactic to a "rapid investment-return" model. Compared to natural forests, planted forest trees exhibit stronger environmental plasticity and greater variability with forest age in their resource utilization strategies. Overall, forest age is the dominant factor influencing resource utilization strategies in both planted and natural forests, having a far greater direct impact than climatic factors (temperature, precipitation, and sunlight) and soil nutrient factors. Additionally, as forest age increases, both planted and natural forests show an increase in SLA and a decrease in LDMC, indicating a gradual shift towards more efficient resource utilization strategies.

Diagnostic Accuracy of MRI in Knee Meniscus Tear and ACL Injury.

Objective: Knee injuries are very common and may lead to other secondary injuries if effective treatment is lacking. In addition to standardized physical examination, magnetic resonance imaging (MRI) is sometimes considered an aid in the diagnosis of knee trauma. In order to have a more accurate diagnosis of knee injuries, we compared MRI with arthroscopic findings in this study to evaluate the diagnostic accuracy of MRI for meniscal tears and anterior cruciate ligament injuries of the knee. Methods: One hundred and ten patients with suspected meniscal tears and anterior cruciate ligament injuries of the knee who were admitted to our hospital from June 2020 to June 2022 were selected as study subjects, and the clinical data of the patients were retrospectively analyzed. All patients underwent MRI for preoperative diagnosis, and the sensitivity, specificity, MRI findings, and confirmation of diagnosis were compared and analyzed, and the accuracy of MRI in diagnosing meniscal tears and ACL injuries of the knee was analyzed. Results: The mean ACL angle was (98.0 ± 5.4) in the MRI group and (118.0 ± 6.8) in the arthroscopic group, the difference between the two groups was statistically significant P < .05. The mean L/H value of the ACL was (2.12 ± 0.38) in the MRI group and (1.81 ± 0.19) in the arthroscopic group, which was statistically different between the two groups (P < .05). Among the patients, 68 meniscal injuries were found in the MRI examination, including 45 cases of knee meniscal tears and 23 cases of anterior cruciate ligament injuries. The sensitivity, specificity, positive and negative predictive values, agreement rate, kappa value, and Youden index of MRI in diagnosing meniscal tears and ACL injuries were all high. Conclusions: In terms of sensitivity and accuracy, MRI is an excellent imaging technique for the diagnosis of meniscal tears and anterior cruciate ligament injuries of the knee.

Climate Factors Affect Above-Belowground Biomass Allocation in Broad-Leaved and Coniferous Forests by Regulating Soil Nutrients.

The allocation of plant biomass above and below ground reflects their strategic resource utilization, crucial for understanding terrestrial carbon flux dynamics. In our comprehensive study, we analyzed biomass distribution patterns in 580 broadleaved and 345 coniferous forests across China from 2005 to 2020, aiming to discern spatial patterns and key drivers of belowground biomass proportion (BGBP) in these ecosystems. Our research revealed a consistent trend: BGBP decreases from northwest to southeast in both forest types. Importantly, coniferous forests exhibited significantly higher BGBP compared to broadleaved forests (p < 0.001). While precipitation and soil nutrients primarily influenced biomass allocation in broadleaved forests, temperature and soil composition played a pivotal role in coniferous forests. Surprisingly, leaf traits had a negligible impact on BGBP (p > 0.05). Climatic factors, such as temperature and rainfall, influenced biomass partitioning in both strata by altering soil nutrients, particularly soil pH. These findings provide valuable insights into understanding carbon sequestration dynamics in forest ecosystems and improving predictions of the future trajectory of this critical carbon cycle component.

Precipitation Dominates the Allocation Strategy of Above- and Belowground Biomass in Plants on Macro Scales.

The allocation of biomass reflects a plant's resource utilization strategy and is significantly influenced by climatic factors. However, it remains unclear how climate factors affect the aboveground and belowground biomass allocation patterns on macro scales. To address this, a study was conducted using aboveground and belowground biomass data for 486 species across 294 sites in China, investigating the effects of climate change on biomass allocation patterns. The results show that the proportion of belowground biomass in the total biomass (BGBP) or root-to-shoot ratio (R/S) in the northwest region of China is significantly higher than that in the southeast region. Significant differences (p < 0.05) were found in BGBP or R/S among different types of plants (trees, shrubs, and herbs plants), with values for herb plants being significantly higher than shrubs and tree species. On macro scales, precipitation and soil nutrient factors (i.e., soil nitrogen and phosphorus content) are positively correlated with BGBP or R/S, while temperature and functional traits are negatively correlated. Climate factors contribute more to driving plant biomass allocation strategies than soil and functional trait factors. Climate factors determine BGBP by changing other functional traits of plants. However, climate factors influence R/S mainly by affecting the availability of soil nutrients. The results quantify the productivity and carbon sequestration capacity of terrestrial ecosystems and provide important theoretical guidance for the management of forests, shrubs, and herbaceous plants.

Climate factors affect forest biomass allocation by altering soil nutrient availability and leaf traits.

Biomass in forests sequesters substantial amounts of carbon; although the contribution of aboveground biomass has been extensively studied, the contribution of belowground biomass remains understudied. Investigating the forest biomass allocation is crucial for understanding the impacts of global change on carbon allocation and cycling. Moreover, the question of how climate factors affect biomass allocation in natural and planted forests remains unresolved. Here, we addressed this question by collecting data from 384 planted forests and 541 natural forests in China. We evaluated the direct and indirect effects of climate factors on the belowground biomass proportion (BGBP). The average BGBP was 31.09% in natural forests and was significantly higher (38.75%) in planted forests. Furthermore, we observed a significant decrease in BGBP with increasing temperature and precipitation. Climate factors, particularly those affecting soil factors, such as pH, strongly affected the BGBP in natural and planted forests. Based on our results, we propose that future studies should consider the effects of forest type (natural or planted) and soil factors on BGBP.

Climate factors determine the utilization strategy of forest plant resources at large scales.

Plant functional traits are a representation of plant resource utilization strategies. Plants with higher specific leaf area (SLA) and lower leaf dry matter content (LDMC) exhibit faster investment-return resource utilization strategies. However, the distribution patterns and driving factors of plant resource utilization strategies at the macroscale are rarely studied. We investigated the relative importance of climatic and soil factors in shaping plant resource utilization strategies at different life forms in forests using data collected from 926 plots across 163 forests in China. SLA and LDMC of plants at different life forms (i.e., trees, shrubs, and herbs) differ significantly. Resource utilization strategies show significant geographical differences, with vegetation in the western arid regions adopting a slower investment-return survival strategy and vegetation in warmer and wetter areas adopting a faster investment-return survival strategy. SLA decreases significantly with increased temperature and reduced rainfall, and vegetation growing in these conditions exhibits conservative resource utilization. Mean annual precipitation (MAP) is a key climatic factor that controls the resource utilization strategies of plants at the macroscale. Plants use resources more conservatively as soil pH increases. The influence of climate and soil factors is coupled to determine the resource utilization strategies of plants occupying different life forms at the macroscale, but the relative contribution of each varies across life forms. Our findings provide a theoretical framework for understanding the potential impact of increasing global temperatures on plant resource utilization.