Journal of Forestry Research最新文献

Abstract

A set of standard chronologies for tree-ring width (TRW), earlywood width (EWW) and latewood width (LWW) in Pinus tabuliformis Carr. along an altitudinal gradient (1450, 1400, and 1350 m a.s.l.) on Baiyunshan Mountain, Central China to analyze the effect of varying temperature and precipitation on growth along the gradient. Correlation analyses showed that at all three altitudes and the TRW and EWW chronologies generally had significant negative correlations with mean and maximum temperatures in the current April and May and with minimum temperatures in the prior July and August, but significant positive correlations with precipitation in the current May. Correlations were generally significantly negative between LWW chronologies and all temperatures in the prior July and August, indicating that the prior summer temperature had a strong lag effect on the growth of P. tabuliformis that increased with altitude. The correlation with the standardized precipitation evapotranspiration index (SPEI) confirmed that wet conditions in the current May promoted growth of TR and EW at all altitudes. Significant altitudinal differences were also found; at 1400 m, there were significant positive correlations between EWW chronologies and SPEI in the current April and significant negative correlations between LWW chronologies and SPEI in the current September, but these correlations were not significant at 1450 m. At 1350 m, there were also significant negative correlations between the TRW and the EWW chronologies and SPEI in the prior October and the current July and between LWW chronology and SPEI in the current August, but these correlations were not significant at 1400 m. Moving correlation results showed a stable response of EWW in relation to the SPEI in the current May at all three altitudes and of LWW to maximum temperature in the prior July–August at 1400 m from 2002 to 2018. The EWW chronology at 1400 m and the LWW chronology at 1450 m were identified as more suitable for climate reconstruction. These results provide a strong scientific basis for forest management decisions and climate reconstructions in Central China.

Quercus arkansana (Arkansas oak) is at risk of becoming endangered, as the total known population size is represented by a few isolated populations. The potential impact of climate change on this species in the near future is high, yet knowledge of its predicted effects is limited. Our study utilized the biomod2 R package to develop habitat suitability ensemble models based on bioclimatic and topographic environmental variables and the known locations of current distribution of Q. arkansana. We predicted suitable habitats across three climate change scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) for 2050, 2070, and 2090. Our findings reveal that the current suitable habitat for Q. arkansana is approximately 127,881 km² across seven states (Texas, Arkansas, Alabama, Louisiana, Mississippi, Georgia, and Florida); approximately 9.5% is encompassed within state and federally managed protected areas. Our models predict that all current suitable habitats will disappear by 2050 due to climate change, resulting in a northward shift into new regions such as Tennessee and Kentucky. The large extent of suitable habitat outside protected areas suggests that a species-specific action plan incorporating protected areas and other areas may be crucial for its conservation. Moreover, protection of Q. arkansana habitat against climate change may require locally and regionally focused conservation policies, adaptive management strategies, and educational outreach among local people.

Needle chlorosis (NC) in Pinus taeda L. systems in Brazil becomes more frequent after second and third harvest rotation cycles. In a study to identify factors contributing to yellowing needle chorosis (YNC), trees were grown in soils originating from contrasting parent materials, and soils and needles (whole, green and chlorotic portions) from 1- and 2-year-old branches and the first and second needle flush release at four sites with YNC on P. taeda were analyzed for various elements and properties. All soils had very low base levels (Ca²⁺, Mg²⁺ and K⁺) and P, suggesting a possible lack of multiple elements. YNC symptoms started at needle tips, then extended toward the needle base with time. First flush needles had longer portions with YNC than second flush needles did. Needles from the lower crown also had more symptoms along their length than those higher in the canopy. Symptoms were similar to those reported for Mg. In chlorotic portions, Mg and Ca concentrations were well below critical values; in particular, Mg levels were only one third of the critical value of 0.3 g kg⁻¹. Collectively, results suggest that Mg deficiency is the primary reason for NC of P. taeda in various parent soils in Brazil.

Abstract

On an agrosilvopastoral farm in central Italy where Maremmana cattle graze in Turkey oak forests, we evaluated the impact of different livestock densities on stand structure, tree diversity and natural regeneration in four types of grazed areas based on the grazing regime adopted: calf-grazed, high-intensity-grazed, low-intensity-grazed, ungrazed control. For each area, we set up three permanent circular plots (radius of 15 m) to survey the structural and dasometric characteristics of the overstorey, understorey, and regeneration layer. The results showed that grazing negatively affected the complexity of the forest structure and its potential to regenerate and maintain a high level of biodiversity. The differences in stand structure observed between the grazing areas were closely related to livestock density. The most sensitive components of the system were the understorey and the regeneration layers. Contrarily, the current grazing management did not affect the dominant tree structure or its composition. Our findings identified medium-term monitoring and regeneration management as the two significant aspects to consider when assessing sustainable livestock. New forests can be established by excluding grazing for about 20–25 years.

Forest fires are natural disasters that can occur suddenly and can be very damaging, burning thousands of square kilometers. Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model, the geographical weighted logistic regression model, the Lasso regression model, the random forest model, and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province. The models, along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area. Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models. The accuracies of the random forest model, the support vector machine model, geographical weighted logistic regression model, the Lasso regression model, and logistic model were 88.7%, 87.7%, 86.0%, 85.0% and 84.6%, respectively. Weather is the main factor affecting forest fires, while the impacts of topography factors, human and social-economic factors on fire occurrence were similar.

Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau. Climate-growth relationship analysis indicated that the two co-existing species reponded similarly to climate factors, although S. saltuaria was more sensitive than A. faxoniana. The strongest correlation was between S. saltuaria chronology and regional mean temperatures from June to November. Based on this relationship, a regional mean temperature from June to November for the period 1605–2016 was constructed. Reconstruction explained 37.3% of the temperature variance during th period 1961–2016. Six major warm periods and five major cold periods were identified. Spectral analysis detected significant interannual and multi-decadal cycles. Reconstruction also revealed the influence of the Atlantic Multi-decadal Oscillation, confirming its importance on climate change on the eastern Tibetan Plateau.

Atmospheric nitrogen (N) deposition is predicted to increase, especially in the subtropics. However, the responses of soil microorganisms to long-term N addition at the molecular level in N-rich subtropical forests have not been clarified. A long-term nutrient addition experiment was conducted in a subtropical evergreen old-growth forest in China. The four treatments were: control, low N (50 kg N ha⁻¹ a⁻¹), high N (100 kg N ha⁻¹ a⁻¹), and combined N and phosphorus (P) (100 kg N ha⁻¹ a⁻¹ + 50 kg P ha⁻¹ a⁻¹). Metagenomic sequencing characterized diversity and composition of soil microbial communities and used to construct bacterial/fungal co-occurrence networks. Nutrient-treated soils were more acidic and had higher levels of dissolved organic carbon than controls. There were no significant differences in microbial diversity and community composition across treatments. The addition of nutrients increased the abundance of copiotrophic bacteria and potentially beneficial microorganisms (e.g., Gemmatimonadetes, Chaetomium, and Aureobasidium). Low N addition increased microbiome network connectivity. Three rare fungi were identified as module hubs under nutrient addition, indicating that low abundance fungi were more sensitive to increased nutrients. The results indicate that the overall composition of microbial communities was stable but not static to long-term N addition. Our findings provide new insights that can aid predictions of the response of soil microbial communities to long-term N addition.

Thinning is an effective management step for sustainable forest development, yet less attention is paid to the restoration of soil microbiota after thinning. In this study, both abundant and rare soil microbial communities (i.e., bacterial, fungal), were evaluated under various thinning treatments in a mixed stand of Cunninghamia lanceolata and Sassafras tzumu using MiSeq sequencing. Thinning did not significantly change either abundant or rare bacterial and fungal community composition, but affected their alpha diversity. The Shannon– Wiener indexes of rare fungal taxa under medium thinning were significantly lower than in the light thinning (P < 0.05 level). Xanthobacteraceae dominated the abundant bacterial taxa, and Saitozyma and Mortierlla the abundant fungal taxa. The most common rare bacterial taxa varied; there was no prevalent rare fungal taxa under different thinnings. In addition, soil available nitrogen, total phosphorus, and pH had significant effects on rare bacterial taxa. Nutrients, especially available phosphorus, but not nitrogen, affected abundant and rare soil fungi. The results indicate that soil properties rather than plant factors affect abundant and rare microbial communities in soils of mixed stands. Thinning, through mediating soil properties, influences both abundant and rare bacterial and fungal communities in the mixed C. lanceolata and S. tzumu stand.