Search Results (12)

Considerable uncertainty exists regarding the overall effects of future climate change on forests in arid mountains, and the elevational range of drought-induced tree growth decline remains unclear. Tianshan is the largest mountain in arid regions globally. Here, we analyzed tree ring data of pure stands of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) in the Jiangbulake region in the eastern Tianshan Mountains along an elevational gradient (1800–2600 m a.s.l.). The radial growth of P. schrenkiana trees declined in three of the nine sample strips (1800–2100 m a.s.l.) over the last two decades. P. schrenkiana growth response (measured by the tree ring width index, RWI) to temperature significantly changed at an elevational “inflection point” at 2100–2200 m. RWI was significantly negatively correlated with temperature at low elevations, whereas the opposite was observed at high elevations. Precipitation and minimum temperatures in winter and spring and mean temperatures in spring and summer were the main drivers of P. schrenkiana growth, with the effect of maximum temperatures on tree growth concentrated in the spring. In addition to climate warming in the study area since the 1970s, tree growth (as measured by the basal area increment, BAI) at elevations below 2200 m initially increased and then decreased. Tree growth at higher elevations continues to increase. Since 2000, the average RWI at high elevations exceeded that at low elevations. The average BAI values at high and low elevations have gradually approached each other in recent decades, although lower elevations exhibited higher values in the past. Full article

Combining tree ring data with remote sensing data can help to gain a deeper understanding of the driving factors that influence vegetation change, identify climate events that lead to vegetation change, and improve the parameters of global vegetation index reconstruction models. However, it is currently not well understood how climate change at different elevations in the central Tianshan Mountains affects radial tree growth and the dynamics of forest canopy growth. We selected Schrenk spruce (Picea schrenkiana) tree core samples from different elevations in the central Tianshan Mountains. We analyzed the relationships of various tree-ring parameters, including tree-ring width, maximum latewood density (MXD), and minimum earlywood density (MID) chronologies, with 1982–2012 GIMMS (Global Inventory Modelling and Mapping Studies) NDVI (Normalized Difference Vegetation Index), 2001–2012 MODIS (moderate resolution imaging spectroradiometer) NDVI, and meteorological data. (1) There were strong correlations between tree-ring width chronologies and the lowest temperatures, especially in July. Tree-ring width chronologies at higher altitudes were positively correlated with temperature; the opposite pattern was observed at lower altitudes. MID chronologies were positively correlated with July temperature in high-altitude areas and mean temperature and highest temperature from May to September in low-altitude areas, and negatively correlated with precipitation during this period. MXD chronologies were mainly negatively correlated with precipitation. MXD chronologies were mainly positively correlated with temperature in April and May. (2) The correlations between MXD chronologies at each sampling point and NDVI in each month of the growing season were strong. Both MID and MXD chronologies were negatively correlated with GIMMS NDVI in July. The overall correlations between tree-ring parameters and MODIS NDVI were stronger than the correlations between tree-ring parameters and GIMMS NDVI in high-altitude areas; the opposite pattern was observed in low-altitude areas. Drought stress may be the main factor affecting tree ring parameters and NDVI. In the future, we should combine tree ring parameters with vegetation index to investigate a larger scale of forests. Full article

With global warming, the frequency, intensity, and period of extreme climates in more areas will probably increase in the twenty first century. However, the impact of climate extremes on forest vulnerability and the mechanisms by which forests adapt to climate extremes are not clear. The eastern Tianshan Mountains, set within the arid and dry region of Central Asia, is very sensitive to climate change. In this paper, the response of Picea schrenkiana and Larix sibirica to climate fluctuations and their stability were analyzed by Pearson’s correlation based on the observation of interannual change rates of climate indexes in different periods. Additionally, their ecological adaptability to future climate change was explored by regression analysis of climate factors and a selection of master control factors using the Lasso model. We found that the climate has undergone significant changes, especially the temperature, from 1958 to 2012. Around 1985, various extreme climate indexes had obvious abrupt changes. The research results suggested that: (1) the responses of the two tree species to extreme climate changed significantly after the change in temperature; (2) Schrenk spruce was more sensitive than Siberian larch to extreme climate change; and (3) the resistance of Siberian larch was higher than that of Schrenk spruce when faced with climate disturbance events. These results indicate that extreme climate changes will significantly interfere with the trees radial growth. At the same time, scientific management and maintenance measures are taken for different extreme weather events and different tree species. Full article

Snow is an important source of freshwater in the Tianshan Mountains of Central Asia. This study established 18 tree ring width chronologies and compound chronologies and analyzed the effects of snow depth, measured both by remote sensing and at meteorological stations, on the radial growth of spruce trees. The results showed that the established standard chronology of tree ring width is suitable for the analysis of tree ring climatology. The correlation coefficient of the ring width index (RWI) and the remote sensing snow depth was greater than that of the meteorological station snow depth. For the remote sensing snow depth, the correlation coefficients were greater in the winter and spring months compare to other periods, while the correlation coefficients of the meteorological stations were greater only in the winter. The nonlinear method (BRNN) showed good fitting in the reconstruction of the historical snow depth. The reconstructed snow depth exhibited a decreasing trend in the Bharakonu Mountains (BM), Narathi Mountains (NM), and Halke mountains (KM) sub-regions in the overall reconstructed period; however, the trends were inconsistent in both the historical and the observed periods, indicating the importance of reconstructing snow depth in the Tianshan Mountains. Full article

Accurately estimating the above-ground biomass (AGB) of spruce forests and analyzing their spatial patterns are critical for quantifying forest carbon stocks and assessing regional climate conditions in China’s drylands, with significant implications for the sustainable management and conservation of forest ecosystems in the Tianshan Mountains. The K-Means clustering algorithm was used to divide 144 measured AGB samples into four AGB classes, combined with remote sensing data from Landsat products, 19 bioclimatic variables, 3 topographical variables, and 3 soil variables to generate probability distributions of four AGB classes using the MaxEnt model. Finally, the spatial distribution of AGB was mapped using the mathematical formulae available in the GIS software. Results indicate that (1) the area under the receiver operating characteristic curve (AUC-ROC) of the AGB models for all classes exceeded 0.8, indicating satisfactory model accuracy; (2) the dominant factors affecting the distribution of different AGB classes varied. The primary dominant factors for the first–fourth AGB classes model were altitude (20.4%), precipitation of warmest quarter (Bio18, 15.7%), annual mean temperature (Bio1, 50.5%), and red band (Band4, 26.7%), respectively, and the response curves indicated that the third AGB model was more tolerant of elevation than the first and second AGB classes; (3) the AGB has a spatial distribution pattern of being higher in the west and low in the east, with a “single-peaked” pattern in terms of latitude, and the average AGB of pixels was 680.92 t·hm⁻²; (4) the correlation coefficient between measured and predicted AGB is 0.613 (p < 0.05), with the average uncertainty of AGB estimation at 39.32%. This study provides valuable insights into the spatial patterns and drivers of AGB in spruce forests in the Tianshan Mountains, which can inform effective forest management and conservation strategies. Full article

Spatial patterns of soil carbon (C), nitrogen (N) and phosphorus (P) and their stoichiometric characteristics (C:N:P) play an important role in nutrient limitations, community dynamics, nutrient use efficiency and biogeochemical cycles, etc. To date, the spatial distributions of soil organic C at various spatial scales have been extensively studied, whereas little is known about the spatial patterns of N and P and C:N:P ratios in various landscapes, especially across complex terrains. To fill this gap, we estimated the spatial patterns of concentrations of soil C, N and P and C:N:P ratios in Schrenk’s spruce (Picea schrenkiana Fisch. & C. A. Mey.) forest in the Tianshan Mountains based on data from soil cores collected from 2012 to 2017, and using the following four regression models: multiple linear regression, stepwise regression, ridge regression and lasso regression. We found the following: (1) elevation and climatic variables jointly contributed to concentrations of C, N and P and C:N:P ratios, (2) soil C, N and P concentrations, and their stoichiometric ratios, demonstrated continual spatial patterns in Schrenk’s spruce forest, (3) Multiple linear regression could be reliably used to estimate the spatial patterns of soil elemental concentrations and stoichiometric ratios in mountainous terrain. We suggest that more independent variables (including biotic, abiotic and anthropogenic factors) should be considered in future works. Additionally, adjustment of multiple linear regression and other models should be used for a better delineation of spatial patterns in the concentrations of soil elements and stoichiometric ratios. Full article

Here, unmanned aerial vehicle (UAV) remote sensing and machine vision were used to automatically, accurately, and efficiently count Tianshan spruce and improve the efficiency of scientific forest management, focusing on a typical Tianshan spruce forest on Tianshan Mountain, middle Asia. First, the UAV in the sampling area was cropped from the image, and a target-labeling tool was used. The Tianshan spruce trees were annotated to construct a data set, and four models were used to identify and verify them in three different areas (low, medium, and high canopy closures). Finally, the combined number of trees was calculated. The average accuracy of the detection frame, mean accuracy and precision (mAP), was used to determine the target detection accuracy. The Faster Region Convolutional Neural Network (Faster-RCNN) model achieved the highest accuracies (96.36%, 96.32%, and 95.54% under low, medium, and high canopy closures, respectively) and the highest mAP (85%). Canopy closure affected the detection and recognition accuracy; YOLOv3, YOLOv4, and Faster-RCNN all showed varying spruce recognition accuracies at different densities. The accuracy of the Faster-RCNN model decreased by at least 0.82%. Combining UAV remote sensing with target detection networks can identify and quantify statistics regarding Tianshan spruce. This solves the shortcomings of traditional monitoring methods and is significant for understanding and monitoring forest ecosystems. Full article

Forest ecosystems are strongly impacted by extreme climate, and the age effects of radial growth under drought can provide profound understanding of the adaptation strategy of a tree species to climate change. Schrenk spruce (Picea schrenkiana Fisch. & C.A. Mey) trees of three age groups (young, middle-aged, and old) were collected to establish the tree-ring width chronologies in the eastern Tianshan Mountains of northwestern China. Meanwhile, we analyzed and compared the response and resistance disparities of radial growth to drought in trees of different age groups. The results showed that (1) drought stress caused by increasing temperatures was the main factor limiting the radial growth of Schrenk spruce, (2) the old and young trees were more susceptible to drought stress than the middle-aged trees, as suggested by the responses of Schrenk spruce trees and based on the SPEI (standardized precipitation evapotranspiration index), and (3) the difference of the resistance indexes (resistance, recovery, resilience, and relative resilience) of three age groups to drought supported that the resistance values were in the order middle age > young age > old age, but the recovery, resilience, and relative resilience values were in the order old age > young age > middle age. These results will provide a basis for the ecological restoration and scientific management of dominant coniferous tree species of different age groups in the sub-alpine forest ecosystems of the arid regions under climate change scenarios. Full article

Global warming and the sharp rise in atmospheric CO₂ concentrations have a profound impact on forest ecosystems. To better manage these changes, a comprehensive understanding of forest ecosystem responses to global change is essential. There is a lack of knowledge about the growth response of Schrenk spruce (Picea schrenkiana Fisch. et Mey)—an endemic tree species found in the arid Central Asian region—to climate change and rising atmospheric CO₂ concentrations. In this study, core samples of Schrenk spruce were collected in the Sayram Lake Basin, Xinjiang. Tree-ring radial growth and long-term intrinsic water-use efficiency (iWUE) chronologies were established based on standard tree-ring width and stable carbon isotope methods. The relationships between atmospheric CO₂ concentrations, climate, radial growth, and iWUE were analyzed. Our results indicate that the iWUE of trees in this region has continued to rise rapidly but that radial growth has not increased over the past 160 years. The main factor affecting iWUE is atmospheric CO₂ concentrations (C_a), whereas the radial growth is much more sensitive to water availability. This may explain why the increase C_a has not had a fertilizer effect on the radial growth of trees. Full article

The divergence problem, which manifests as an unstable response relationship between tree-ring growth and climatic factors under the background of global warming, poses a challenge to both the traditional theory of dendroclimatology and the reliability of climatic reconstructions based on tree-ring data. Although Schrenk spruce, as the dominant tree species in the Tianshan Mountains, is frequently applied in the dendrochronological studies, the understanding of the divergence problem of this tree species is still limited. This study conducted correlation analysis between climatic factors and tree-ring width chronologies from 51 living and healthy specimens of Schrenk spruce at sites of high and low elevation in the Alatau Mountains to determine the stability of the response. The results revealed that the tree-ring width of the spruce specimens was correlated positively with precipitation and correlated negatively with temperature. Although the variations of the two tree-ring chronologies were similar, the radial growth of the spruce at the low elevation was found more sensitive to climatic factors. Furthermore, the sensitivity of tree growth to climate demonstrated an obvious increase after an abrupt change of climate under the background of the recent warming and wetting trend. Increased drought stress, calculated based on climatic data, was regarded as the main reason for this phenomenon. The results supply the gap of the stability of climatic response of tree growth in Central Asia to some extent. Full article

The Chu River is one of the most important rivers in arid Central Asia. Its discharge is affected by climate change. Here, we establish a tree-ring chronology for the upper Chu River Basin and analyze the relationships between radial growth, climate, and discharge. The results show that the radial growth of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) is controlled by moisture. We also reconstruct a 175-year standardized precipitation-evapotranspiration index (SPEI) for the Chu River Basin. A comparison of the reconstructed and observed indices reveal that 39.5% of the variance occurred during the calibration period of 1952–2014. The SPEI reconstruction and discharge variability of the Chu River show consistent long-term change. They also show that the Chu River Basin became increasingly dry between the 1840s and the 1960s, with a significant drought during the 1970s. A long and rapid wetting period occurred between the 1970s and the 2000s, and was followed by increasing drought since 2004. The change in the SPEI in the Chu River Basin is consistent with records of long-term precipitation, SPEI and Palmer Drought Severity Indices (PDSI) in other proximate regions of the western Tianshan Mountains. The hydroclimatic change of the Chu River Basin may be associated with westerly wind. This study is helpful for disaster prevention and water resource management in arid central Asia. Full article

The climate changed from warm-dry to warm-wet during the 1960s in northwest China. However, the effects of climate change on the response of radial growth from different age-class trees have been unclear. We assessed the age-effect radial growth responses in three age-classes (ml-old: ≥200 years, ml-middle: 100–200 years and ml-young: <100 years) of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) in the eastern Tianshan Mountains. The primary conclusions were as follows: the developed chronologies of the three age-class trees contained significant climate information and exhibited high similarity as shown by calculating the statistical parameter characteristics and Gleichlaufigkeit index. The three age-class trees were consistent for annual variation trends of radial growth under climate change, showing similar fluctuations, tree-ring width chronology trends, time trends of cumulative radial growth, and basal area increment. In addition, the old and middle trees were found to be more sensitive to climate variability by analyzing Pearson correlations between radial growth from three age-class trees and climate factors. As a result, the drought caused by reduced total precipitation and higher mean temperature was a limiting factor of tree radial growth, and the trees with ages of up to 100 years were more suitable for studies on the growth-climate relationships. Thus, the studies on age-effect radial growth responses of Schrenk spruce can help not only in understanding the adaptive strategies of different-age trees to climate change, but also provide an accurate basis for climate reconstruction. Full article