Tree Line Identification and Dynamics under Climate Change in Wuyishan National Park Based on Landsat Images

Climate Change and Topography Drive the Expansion of Betula ermanii in the Alpine Treeline Ecotone of the Changbai Mountain

Alpine treelines ecotones are critical ecological transition zones and are highly sensitive to global warming. However, the impact of climate on the distribution of treeline trees is not yet fully understood as this distribution may also be affected by other factors. Here, we used high-resolution satellite images with climatic and topographic variables to study changes in treeline tree distribution in the alpine treeline ecotone of the Changbai Mountain for the years 2002, 2010, 2017, and 2021. This study employed the Geodetector method to analyze how interactions between climatic and topographic factors influence the expansion of Betula ermanii on different aspect slopes. Over the past 20 years, B. ermanii, the only tree species in the Changbai Mountain tundra zone, had its highest expansion rate from 2017 to 2021 across all the years studied, approaching 2.38% per year. In 2021, B. ermanii reached its uppermost elevations of 2224 m on the western aspects and 2223 m on the northern aspects, which are the predominant aspects it occupies. We also observed a notable increase in the distribution of B. ermanii on steeper slopes (> 15°) between 2002 and 2021. Moreover, we found that interactions between climate and topographic factors played a more significant role in B. ermanii's expansion than any single dominant factor. Our results suggest that the interaction between topographic wetness index and the coldest month precipitation (Pre1), contributing 91% of the observed variability, primarily drove the expansion on the southern aspect by maintaining soil moisture, providing snowpack thermal insulation which enhanced soil temperatures, decomposition, and nutrient release in harsh conditions. On the northern aspect, the interaction between elevation and mean temperature of the warmest month explained 80% of the expansion. Meanwhile, the interaction between Pre1 and mean temperature of the growing season explained 73% of the expansion on the western aspect. This study revealed that dominant factors driving treeline upward movement vary across different mountain aspects. Climate and topography play significant roles in determining tree distribution in the alpine treeline ecotone. This knowledge helps better understand and forecast treeline dynamics in response to global climate change.

Global distribution and climatic controls of natural mountain treelines

Mountain treelines are thought to be sensitive to climate change. However, how climate impacts mountain treelines is not yet fully understood as treelines may also be affected by other human activities. Here, we focus on "closed-loop" mountain treelines (CLMT) that completely encircle a mountain and are less likely to have been influenced by human land-use change. We detect a total length of ~916,425 km of CLMT across 243 mountain ranges globally and reveal a bimodal latitudinal distribution of treeline elevations with higher treeline elevations occurring at greater distances from the coast. Spatially, we find that temperature is the main climatic driver of treeline elevation in boreal and tropical regions, whereas precipitation drives CLMT position in temperate zones. Temporally, we show that 70% of CLMT have moved upward, with a mean shift rate of 1.2 m/year over the first decade of the 21st century. CLMT are shifting fastest in the tropics (mean of 3.1 m/year), but with greater variability. Our work provides a new mountain treeline database that isolates climate impacts from other anthropogenic pressures, and has important implications for biodiversity, natural resources, and ecosystem adaptation in a changing climate.

Effects of Landscape Context on Bird Community in the Subtropical Evergreen Broad-Leaved Forest of Wuyishan National Park

Landscape context can reflect the habitat structure and play an important role in bird species occurrences and abundance. For local biodiversity conservation and restoration, we examined the effects of landscape context on bird communities at different altitude gradients. Our study was conducted in four altitude gradients (<300 m, 300-599 m, 600-899 m, 900-1200 m) of subtropical evergreen broad-leaved forest in Wuyishan National Park, China. The bird survey was carried out in 115 transects in spring, summer, autumn and winter. We examined the effects of altitude, season and landscape context. The result showed that (1) species richness and abundance at <300 m altitude were highest among the four altitude gradients, and they showed more significant differences than those at other altitude gradients; (2) the species richness of birds was associated with altitude, season and landscape context, as the season is more significant than other explanatory variables; (3) at the landscape level, habitat configuration is more important. The average canopy height and contagion index positively correlated with the species richness and abundance of birds at all four altitude gradients. In particular, the average canopy height is significant at 300-599 m and 600-899 m altitude gradients. The study results can provide a theoretical basis and guidance for future national park conservation and management and ecological restoration in the subtropical evergreen broad-leaved forest regions.

Shoreline Dynamics of Chongming Island and Driving Factor Analysis Based on Landsat Images

Chongming Island, the third largest island in China, has experienced dramatic shoreline changes due to erosion, river deposits, and human activities. While previous studies have shown the capacity of Landsat series images to extract shoreline dynamics, the spatial variation of shoreline dynamics and their corresponding driving factors remain unclear. Therefore, we established a method to monitor the shoreline dynamics of Chongming Island from 1984 to 2020 and to evaluate the driving factors of shoreline changes using a novel approach to Landsat image analysis. The method, based on the LISA (local indicator of spatial autocorrelation) concept, automatically extracted the shoreline from Landsat imagery. The results show that the LISA method, based on the SWIR1 band, has a high capacity for shoreline extraction in Chongming Island. By distinguishing the responses of the eastern and northern shorelines to upstream sediment loads and comprehensively analyzing the driving factors of eastern and northern dynamics, we found that: (i) although upstream sediment loads decreased dramatically, the shoreline of Chongming Island is still expanding due to human activities (i.e., reclamation and an estuary project) and sediment re-suspension from near-shore or cross-shore currents; (ii) the expansion of Chongming Island was initially due to the dynamics at the eastern shoreline, but the expansion of the eastern shoreline slowed after 2008 as upstream sedimentation slowed, less construction of cofferdams took place, and the Qingcaosha Reservoir was constructed; (iii) the northern shoreline of Chongming Island expanded rapidly after 1999, due to the merger of Xinlongsha, Xincunsha, and Chongming Island, and the transport of coastal and offshore sediments by hydrodynamic processes; and (iv) the main driving factors of eastern shoreline movement on Chongming Island are cofferdam reclamation and coastal engineering, and the changes at the northern shoreline are mainly affected by reclamation projects, offshore sediment supplies, and upstream sediment inflow. The results of this study provide theoretical fundamentals for land reclamation and future urban planning for Chongming Island.

The Impact of NPV on the Spectral Parameters in the Yellow-Edge, Red-Edge and NIR Shoulder Wavelength Regions in Grasslands

Even though research has shown that the spectral parameters of yellow-edge, red-edge and NIR (near-infrared) shoulder wavelength regions are able to estimate green cover and leaf area index (LAI), a large amount of dead materials in grasslands challenges the accuracy of their estimation using hyperspectral remote sensing. However, the exact impact of dead vegetation cover on these spectral parameters remains unclear. Therefore, we evaluated the influences of dead materials on the spectral parameters in the wavelength regions of yellow-edge, red-edge and NIR shoulder by comparing normalized difference vegetation indices (NDVI) including the common red valley at 670 nm and NDVI using the red valley extracted by a new statistical method. This method, based on the concept of segmented linear regression, was developed to extract the spectral parameters and calculate NDVI automatically from the hyper-spectra. To fully understand the impact of dead cover on the spectral parameters (i.e., consider full coverage combinations of green vegetation, dead materials and bare soil), both in situ measured and simulated hyper-spectra were analyzed. The impact of dead cover on LAI estimation by those spectral parameters and NDVI were also evaluated. The results show that: (i) without considering the influence of bare soil, dead materials decreases the slope of red-edge, the slope of NIR shoulder and NDVI, while dead materials increases the slope of yellow-edge; (ii) the spectral characteristics of red valley disappear when dead cover exceeds 67%; (iii) large amount of dead materials also result in a blue shift of the red-edge position; (iv) accurate extraction of the red valley position enhances LAI estimation and reduces the influences of dead materials using hyperspectral NDVI; (v) the accuracy of LAI estimation using the slope of yellow-edge, the slope of red-edge, red-edge position and NDVI significantly drops when dead cover exceeds 72.3–74.5% (variation among indices).

Fifty Years of Change in a Coniferous Forest in the Qilian Mountains, China—Advantages of High-Definition Remote Sensing

Mountain ecosystems are significantly affected by climate change. However, due to slow vegetation growth in mountain ecosystems, climate-induced vegetation shifts are difficult to detect with low-definition remote sensing images. We used high-definition remote sensing data to identify responses to climate change in a typical Picea crassifolia Kom. forest in the Qilian Mountains, China, from 1968 to 2017. We found that: (1) Picea crassifolia Kom. forests were distributed in small patches or strips on shaded and partly shaded slopes at altitudes of 2700–3250 m, (2) the number, area, and concentration of forest patches have been increasing from 1968 to 2017 in relatively flat and partly sunny areas, but the rate of area increase and ascend of the tree line slowed after 2008, and (3) the establishment of plantation forests may be one of the reasons for the changes. The scale of detected change in Picea crassifolia Kom.forest was about or slightly below 30 m, indicating that monitoring with high-resolution remote sensing data will improve detectability and accuracy.