Road dust biases NDVI and alters edaphic properties in Alaskan arctic tundra

Climate-induced hydrological fluctuations shape Arctic Alaskan peatland plant communities

Rapidly increasing temperatures in high-latitude regions are causing major changes in wetland ecosystems. To assess the impact of concomitant hydroclimatic fluctuations, mineral deposition, and autogenous succession on the rate and direction of changing arctic plant communities in Arctic Alaska, we conducted detailed palaeoecological analyses using plant macrofossil, pollen, testate amoebae, elemental analyses, and radiocarbon and lead (210Pb) dating on two replicate monoliths from a peatland that developed in a river valley on the northern foothills of the Books Range. We observed an expansion of Sphagnum populations and vascular plants preferring dry habitats, such as Sphagnum warnstorfii, Sphagnum teres/squarrosum, Polytrichum strictum, Aulacomnium palustre and Salix sp., in recent decades between 2000 and 2015 CE, triggered by an increase in temperature and deepening water tables. Deepening peatland water tables became accentuated over the last two decades, when it reached its lowest point in the last 700 years. Conversely, a higher water-table between ca. 1500 and 1950 CE led to a recession of Sphagnum communities and an expansion of sedges. The almost continuous supply of mineral matter during this time led to a dominance of minerotrophic plant communities, although with varying species composition throughout the study period. The replicate cores show similar patterns, but nuanced differences are also visible, depicting fine spatial scale differences particularly in peat-forming plant distribution and the different timings of their presence. In conclusion, our study provides valuable insights into the impact of hydroclimatic fluctuations on peatland vegetation in Arctic Alaska, highlighting their tendency to dry out in recent decades. It also highlights the importance of river valley peatlands in paleoenvironmental reconstructions.

Preparation of biomimetic non-iridescent structural color based on polystyrene-polycaffeic acid core-shell nanospheres

Caffeic acid (CA), as a natural plant-derived polyphenol, has been widely used in surface coating technology in recent years due to its excellent properties. In this work, caffeic acid was introduced into the preparation of photonic band gap materials. By controlling the variables, a reasonable preparation method of polystyrene (PS) @polycaffeic (PCA)–Cu(ii) core–shell microspheres was achieved: 1 mmol L⁻¹ cupric chloride anhydrous (CuCl₂), 3 mmol L⁻¹ sodium perborate tetrahydrate (NaBO₃·4H₂O), 2 mmol L⁻¹ CA and 2 g L⁻¹ polystyrene (PS) were reacted at 50 °C for 10 min to prepare PS@PCA–Cu(ii) core–shell microspheres through rapid oxidative polymerization of CA coated PS of different particle diameters. The amorphous photonic crystal structure was self-assembled through thermal assisted-gravity sedimentation, resulting in structural color nanomaterials with soft and uniform color, no angle dependence, stable mechanical fastness and excellent UV resistance.

Caffeic acid (CA), as a natural plant-derived polyphenol, has been widely used in surface coating technology in recent years due to its excellent properties.

Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.

A Spatial and Temporal Assessment of Vegetation Greening and Precipitation Changes for Monitoring Vegetation Dynamics in Climate Zones over Africa

Vegetation is vital, and its greening depends on access to water. Thus, precipitation has a considerable influence on the health and condition of vegetation and its amount and timing depend on the climatic zone. Therefore, it is extremely important to monitor the state of vegetation according to the movements of precipitation in climatic zones. Although a lot of research has been conducted, most of it has not paid much attention to climatic zones in the study of plant health and precipitation. Thus, this paper aims to study the plant health in five African climatic zones. The linear regression model, the persistence index (PI), and the Pearson correlation coefficients were applied for the third generation Normalized Difference Vegetation Index (NDVI3g), with Climate Hazard Group infrared precipitation and Climate Change Initiative Land Cover for 34 years (1982 to 2015). This involves identifying plants in danger of extinction or in dramatic decline and the relationship between vegetation and rainfall by climate zone. The forest type classified as tree cover, broadleaved, deciduous, closed to open (>15%) has been degraded to 74% of its initial total area. The results also revealed that, during the study period, the vegetation of the tropical, polar, and warm temperate zones showed a higher rate of strong improvement. Although arid and boreal zones show a low rate of strong improvement, they are those that experience a low percentage of strong degradation. The continental vegetation is drastically decreasing, especially forests, and in areas with low vegetation, compared to more vegetated areas, there is more emphasis on the conservation of existing plants. The variability in precipitation is excessively hard to tolerate for more types of vegetation.

Experimental and Numerical Investigation of Dustfall Effect on Remote Sensing Retrieval Accuracy of Chlorophyll Content

Chlorophyll is the dominant pigment in the photosynthetic light-harvesting complexes that is related to the physiological function of leaves and is responsible for light absorption and energy transfer. Dust pollution has become an environmental problem in many areas in China, indicating that accurately estimating chlorophyll content of vegetation using remote sensing for assessing the vegetation growth status in dusty areas is vital. However, dust deposited on the leaf may affect the chlorophyll content retrieval accuracy. Thus, quantitatively studying the dustfall effect is essential. Using selected vegetation indices (VIs), the medium resolution imaging spectrometer terrestrial chlorophyll index (MTCI), and the double difference index (DD), we studied the retrieval accuracy of chlorophyll content at the leaf scale under dusty environments based on a laboratory experiment and spectra simulation. First, the retrieval accuracy under different dustfall amounts was studied based on a laboratory experiment. Then, the relationship between dustfall amount and fractional dustfall cover (FDC) was experimentally analyzed for spectra simulation of dusty leaves. Based on spectral data simulated using a PROSPECT-based mixture model, the sensitivity of VIs to dust under different chlorophyll contents was analyzed comprehensively, and the MTCI was modified to reduce its sensitivity to dust. The results showed that (1) according to experimental investigation, the DD model provides low retrieval accuracy, the MTCI model is highly accurate when the dustfall amount is less than 80 g/m², and the retrieval accuracy decreases significantly when the dustfall amount is more than 80 g/m²; (2) a logarithmic relationship exists between FDC and dustfall amount, and the PROSPECT-based mixture model can simulate the leaf spectra under different dustfall amounts and different chlorophyll contents with a root mean square error of 0.015; and (3) according to numerical investigation, MTCI's sensitivity to dust in the chlorophyll content range of 25 to 60 μg/cm² is lower than in other chlorophyll content ranges; DD's sensitivity to dust was generally high throughout the whole chlorophyll content range. These findings may contribute to quantitatively understanding the dustfall effect on the retrieval of chlorophyll content and would help to accurately retrieve chlorophyll content in dusty areas using remote sensing.