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21 pages, 6503 KiB  
Article
Tree Species Diversity and Tree Growth Affected Element Compositions in Glomalin-Related Soil Protein–Soil pH Interaction
by Qianru Ji, Guanchao Cheng, Xu Zhang, Wenjie Wang, Xiaorui Guo and Huimei Wang
Sustainability 2025, 17(2), 801; https://doi.org/10.3390/su17020801 (registering DOI) - 20 Jan 2025
Abstract
Glomalin-related soil protein (GRSP), a glycoprotein derived from mycorrhizal fungal hyphae, is a mixture of substances rich in various elements essential for plant growth. However, the impacts of tree diversity and forest structure on the element content and storage of GRSP are not [...] Read more.
Glomalin-related soil protein (GRSP), a glycoprotein derived from mycorrhizal fungal hyphae, is a mixture of substances rich in various elements essential for plant growth. However, the impacts of tree diversity and forest structure on the element content and storage of GRSP are not well understood. To investigate this, we collected soil samples from 720 plots (10 m × 10 m) and determined the relative content and storage of elements (C, N, O, Si, P, Fe, Al, Na, Mg, Ca, and K) in GRSP. Additionally, the tree diversity, tree size and density, tree assemblage, and soil physicochemical properties were determined. The results show the following: (1) Plots with lower diversity had 1.27 times higher storage of 11 elements in GRSP compared to those with higher diversity. Plots with higher soil electrical conductance (EC) plots had 28–35% higher storage of 11 elements in GRSP. (2) The relative content of Na, C, and N in GRSP showed a positive relationship with pH, while they exhibited a negative relationship with soil EC, available phosphorus (AP), and tree density. Other elements generally showed contrasting patterns. (3) Path analysis reveals that tree diversity and tree growth had stronger effects on the elemental composition of GRSP than tree spatial assemblage. The magnitude of the driving path coefficients depended on the factors closely related to soil pH. This study demonstrates that the elemental composition of GRSP can be dynamically affected by tree diversity and stand structure, with soil pH playing a crucial interactive role. Full article
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Figure 1

Figure 1
<p>Overview of the hypotheses. It is assumed that the variations in the storage and relative content of elements in glomalin are regulated by the diversity, spatial structure, and community structure of forests. Additionally, soil properties are considered significant interactors regulating this process.</p>
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<p>The linear fitting of soil pH and TG and its elemental storage.</p>
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<p>Pearson correlations and cluster analysis of the relative content of 11 elements in TG and various independent parameters. Two groups could be classified: elements positively related to pH (red-dash rectangular) and elements negatively correlated with pH (blue-dash rectangular). ** means <span class="html-italic">p</span> &lt; 0.01. The red letters on the bottom row represent the average of the relative content of 11 elements in TG.</p>
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<p>Redundancy ordination analysis of the complex relations between various factors, elemental storage, and relative content (<b>a</b>) and explaining powers of different variables (<b>b</b>). Element/TG was the relative content of 11 elements in TG. Eleven elements were the storage of elements in TG.</p>
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<p>The PLS-PM models of each factor on the storage of 11 elements and their relative content in TG. Based on the results from <a href="#sec3dot1-sustainability-17-00801" class="html-sec">Section 3.1</a>, <a href="#sec3dot2-sustainability-17-00801" class="html-sec">Section 3.2</a>, <a href="#sec3dot3-sustainability-17-00801" class="html-sec">Section 3.3</a>, <a href="#sec3dot4-sustainability-17-00801" class="html-sec">Section 3.4</a>, <a href="#sec3dot5-sustainability-17-00801" class="html-sec">Section 3.5</a>, <a href="#sec3dot6-sustainability-17-00801" class="html-sec">Section 3.6</a> and <a href="#sec3dot7-sustainability-17-00801" class="html-sec">Section 3.7</a>, plant diversity traits used in this model are SP and SW, and structural traits are DBH, UBH, SD, M, and W. In addition, the soil properties are pH, EC, and AP. pH↑ represents the relative content of the element positively correlated with soil pH; pH↓ represents the relative content of the element negatively correlated with soil pH. The model was assessed using the Goodness of Fit (GoF). The statistical value was 0.6556. *: <span class="html-italic">p</span> &lt; 0.05, and **: <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>An example of the X-ray photoelectron spectroscopy (XPS)-based analysis of element concentration in purified TG.</p>
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<p>The linear fitting plots between plant diversity (Simpson index), tree diameter (DBH), forest stand density (SD), and GRSP parameters. There was a total of 48 sets of data, of which 20 sets of data were linearly correlated at <span class="html-italic">p</span> &lt; 0.05 and are displayed above.</p>
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<p>The linear fitting of soil properties and TG amounts and the storage of 11 elements in the TG. Note: There was a total of 48 sets of data, of which 24 sets of data were linearly correlated (<span class="html-italic">p</span> &lt; 0.05) and are displayed above.</p>
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<p>Variation partitioning among tree diversity, forest structure, and soil properties.</p>
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21 pages, 13227 KiB  
Article
Dynamic Characteristics and Environmental Driving Factors of Phytoplankton Communities in Plateau Rivers: The Case of the Lhasa River
by Su-Xing Fu, Qiu-Fu Huang, Jun-Ting Li, He Gao, Fei Liu, Yu-Ting Duan, He-Jiao Li, Yin-Hua Zhou, Rong-Rong Liao, Luo Lei, Jian Su, Chao-Wei Zhou and Hai-Ping Liu
Water 2025, 17(2), 283; https://doi.org/10.3390/w17020283 - 20 Jan 2025
Abstract
The dynamic changes in plateau river ecosystems and the driving mechanisms of environmental factors have garnered significant attention. Phytoplankton, a core component of aquatic ecosystems, can directly reflect changes in the aquatic environment. This study focuses on the phytoplankton in the Lhasa River [...] Read more.
The dynamic changes in plateau river ecosystems and the driving mechanisms of environmental factors have garnered significant attention. Phytoplankton, a core component of aquatic ecosystems, can directly reflect changes in the aquatic environment. This study focuses on the phytoplankton in the Lhasa River Basin, including the riverbed from the source to the river mouth, five largest tributaries, and two adjacent wetlands. We analyzed the spatial and temporal variation characteristics of phytoplankton and explored the environmental driving mechanisms based on four field surveys conducted between September 2019 and March 2021. Results showed that a total of 127 species of phytoplankton from six algal phyla were identified, including Cyanobacteria. Among these, Bacillariophyta was the dominant group, accounting for 41.7% of the identified species. Spatially, phytoplankton diversity showed a decreasing trend from upstream to downstream while temporally peaking in spring and autumn. Redundancy analysis revealed that upstream phytoplankton were driven by total hardness and altitude, midstream by pH and potassium ions, and downstream by nitrate and ammonium nitrogen. Classification and regression tree analysis showed total hardness, magnesium ions, and nitrite were key factors influencing phytoplankton abundance, diversity, and evenness. This study highlights the ecological dynamics and driving mechanisms of phytoplankton communities in the Lhasa River, demonstrating their high sensitivity to environmental factors. These findings could help to establish phytoplankton as critical indicators of aquatic ecosystem health and provide scientific guidance for the conservation and management of the plateau river ecosystems. Full article
(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)
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Figure 1
<p>Distribution of sampling sites in the Lhasa River Basin.</p>
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<p>Distributions of phytoplankton diversity in the Lhasa River Basin.</p>
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<p>Temporal and spatial variations of phytoplankton density and biomass in the Lhasa River Basin. (<b>a</b>) phytoplankton density, (<b>b</b>) phytoplankton biomass.</p>
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<p>Temporal and spatial variations of phytoplankton biodiversity index in the Lhasa River Basin. (<b>a</b>) temporal variations, (<b>b</b>) spatial variations.</p>
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<p>The correlation between phytoplankton community structure and environmental factors in the Lhasa River Basin, (<b>A</b>) September 2019, (<b>B</b>) June 2020, (<b>C</b>) November 2020, and (<b>D</b>) March 2021.</p>
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<p>Redundancy analysis sorting graph ((<b>a</b>) upstream, (<b>b</b>) midstream, (<b>c</b>) downstream, and (<b>d</b>) wetland).</p>
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<p>Relationship between total abundance (<b>a</b>), Shannon-Wiener diversity index (<b>b</b>), Pielou evenness index (<b>c</b>) of phytoplankton and environment factors in Lhasa River based on CART.</p>
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15 pages, 4484 KiB  
Article
Identification of HXK Gene Family and Expression Analysis of Salt Tolerance in Buchloe dactyloides
by Haole Qi, Sining Wang, Yuehan Liu, Xueping Wang, Xiaoxia Li and Fengling Shi
Int. J. Mol. Sci. 2025, 26(2), 838; https://doi.org/10.3390/ijms26020838 (registering DOI) - 20 Jan 2025
Viewed by 79
Abstract
Buchloe dactyloides is one of the typical ecological grass species, characterized by its strong salt tolerance. Hexokinase (HXK) plays a crucial role in plant growth, development, and resistance to abiotic stresses. To understand the function of HXKs in the salt tolerance of B. [...] Read more.
Buchloe dactyloides is one of the typical ecological grass species, characterized by its strong salt tolerance. Hexokinase (HXK) plays a crucial role in plant growth, development, and resistance to abiotic stresses. To understand the function of HXKs in the salt tolerance of B. dactyloides, this study identified and analyzed the HXK gene family members using the whole-genome data of B. dactyloides. Additionally, transcriptomic methods were employed to investigate the expression levels and stress response patterns of the HXK family genes under salt stress. The results showed that 25 HXK genes were identified in the B. dactyloides HXK gene family, which were classified into three subfamilies based on the phylogenetic tree. Members within the same subfamily exhibited similar gene structures and conserved motifs. The promoter regions of BdHXKs contained numerous cis-regulatory elements associated with plant hormone responses, plant growth and development, and resistance to abiotic stresses. Quantitative real-time PCR analysis provided preliminary evidence that the BdHXK5, BdHXK7, and BdHXK23 genes might play important roles in the salt tolerance regulation of B. dactyloides. These findings offer a theoretical foundation for further elucidating the functions and molecular regulatory mechanisms of BdHXKs under salt stress. This study has provided a theoretical basis for the breeding of new varieties of ecological restoration grasses with stronger salt tolerance and better growth and development. This is of great significance for the improvement and ecological restoration of saline–alkali land. Full article
(This article belongs to the Special Issue Molecular Research in Bamboo, Tree, Grass, and Other Forest Products)
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Figure 1

Figure 1
<p>Chromosome distribution and gene structure of <span class="html-italic">HXK</span> family genes in <span class="html-italic">Buchloe dactyloides.</span> (<b>A</b>) A total of 8 chromosomes with varying lengths are shown in relation to the Mb (million base pair) scale on the left, and individual chromosomes (bars) are labeled with respective <span class="html-italic">BdHXK</span> genes. (<b>B</b>) Genetic structure analysis of <span class="html-italic">BdHXK</span>s gene family members, with exons represented by yellow rectangles and introns represented by black lines.</p>
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<p>Phylogenetic trees, conserved domain, and conserved motif of <span class="html-italic">HXK</span> family members for <span class="html-italic">Buchloe dactyloides</span>. (<b>A</b>) Phylogenetic tree was constructed based on <span class="html-italic">HXK</span> sequences of <span class="html-italic">Buchloe dactyloides</span>, <span class="html-italic">Arabidopsis thaliana</span>, <span class="html-italic">Oryza sativa</span>, <span class="html-italic">Zea mays</span>, <span class="html-italic">Solanum lycopersicum</span>, and <span class="html-italic">Brachypodium distachyon</span>. The tree was then categorized into four groups, each represented by a distinct color. (<b>B</b>) Conserved domain analysis of <span class="html-italic">Buchloe dactyloides HXK</span> gene family members. (<b>C</b>) Evolutionary relationship of <span class="html-italic">HXK</span> gene family in <span class="html-italic">Buchloe dactyloides</span>. (<b>D</b>) A total of 10 motifs were identified, represented by rectangles of different colors.</p>
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<p>Expression pattern of <span class="html-italic">HXK</span> gene in <span class="html-italic">Buchloe dactyloides</span> under salt stress. The horizontal coordinate is the processing time, and the vertical coordinate is the relative expression level. Duncan’s test of SPSS was used to determine the significance of the differences. Different letters indicate significant differences between groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3 Cont.
<p>Expression pattern of <span class="html-italic">HXK</span> gene in <span class="html-italic">Buchloe dactyloides</span> under salt stress. The horizontal coordinate is the processing time, and the vertical coordinate is the relative expression level. Duncan’s test of SPSS was used to determine the significance of the differences. Different letters indicate significant differences between groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Expression differential of <span class="html-italic">Buchloe dactyloides HXK</span> key gene in different tissues. The expression profiles of the <span class="html-italic">BdHXK5</span>, <span class="html-italic">BdHXK6</span>, <span class="html-italic">BdHXK7</span>, and <span class="html-italic">BdHXK23</span> genes under different tissues and different durations of salt stress treatment are presented in a heatmap. In the heatmap, the color ranging from blue to red indicates the expression levels from low to high, with the specific expression amounts shown as numerical values. On the left side is the expression level of the key genes in roots at different periods, and on the right side is the expression level in leaves at different periods.</p>
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<p><span class="html-italic">Buchloe dactyloides HXK</span> key gene cis-acting element. Different cis-acting elements are represented in different colors. These cis-acting elements may be related to plant stress resistance and hormone regulation.</p>
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<p><span class="html-italic">Buchloe dactyloides BdHXK5</span>, <span class="html-italic">BdHXK6</span>, <span class="html-italic">BdHXK7</span>, and <span class="html-italic">BdHXK23</span> genes’ correlation network analysis in leaves and roots. The ovals represent each gene. The darker the color, the higher the number of interactions with other genes. Edges represent interactions between genes.</p>
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19 pages, 2455 KiB  
Article
Species Diversity, Biomass Production and Carbon Sequestration Potential in the Protected Area of Uttarakhand, India
by Geetanjali Upadhyay, Lalit M. Tewari, Ashish Tewari, Naveen Chandra Pandey, Sheetal Koranga, Zishan Ahmad Wani, Geeta Tewari and Ravi K. Chaturvedi
Plants 2025, 14(2), 291; https://doi.org/10.3390/plants14020291 - 20 Jan 2025
Viewed by 100
Abstract
Ecosystem functioning and management are primarily concerned with addressing climate change and biodiversity loss, which are closely linked to carbon stock and species diversity. This research aimed to quantify forest understory (shrub and herb) diversity, tree biomass and carbon sequestration in the Binsar [...] Read more.
Ecosystem functioning and management are primarily concerned with addressing climate change and biodiversity loss, which are closely linked to carbon stock and species diversity. This research aimed to quantify forest understory (shrub and herb) diversity, tree biomass and carbon sequestration in the Binsar Wildlife Sanctuary. Using random sampling methods, data were gathered from six distinct forest communities. The study identified 271 vascular plants from 208 genera and 74 families. A notable positive correlation (r2 = 0.085, p < 0.05) was observed between total tree density and total tree basal area (TBA), shrub density (r2 = 0.09), tree diversity (D) (r2 = 0.58), shrub diversity (r2 = 0.81), and tree species richness (SR) (r2 = 0.96). Conversely, a negative correlation was found with the concentration of tree dominance (CD) (r2 = 0.43). The Quercus leucotrichophora, Rhododendron arboreum and Quercus floribunda (QL-RA-QF) community(higher altitudinal zone) exhibited the highest tree biomass (568.8 Mg ha−1), while the (Pinus roxburghii and Quercus leucotrichophora) PR-QL (N) community (lower altitudinal zone) in the north aspect showed the lowest (265.7 Mg ha−1). Carbon sequestration was highest in the Quercus leucotrichophora, Quercus floribunda and Rhododendron arboreum (QL-QF-RA) (higher altitudinal zone) community (7.48 Mg ha−1 yr−1) and lowest in the PR-QL (S) (middle altitudinal zone) community in the south aspect (5.5 Mg ha−1 yr−1). The relationships between carbon stock and various functional parameters such as tree density, total basal area of tree and diversity of tree showed significant positive correlations. The findings of the study revealed significant variations in the structural attributes of trees, shrubs and herbs across different forest stands along altitudinal gradients. This current study’s results highlighted the significance of wildlife sanctuaries, which not only aid in wildlife preservation but also provide compelling evidence supporting forest management practices that promote the planting of multiple vegetation layers in landscape restoration as a means to enhance biodiversity and increase resilience to climate change. Further, comprehending the carbon storage mechanisms of these forests will be critical for developing environmental management strategies aimed at alleviating the impacts of climate change in the years to come. Full article
(This article belongs to the Special Issue Plant Functional Diversity and Nutrient Cycling in Forest Ecosystems)
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Graphical abstract

Graphical abstract
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<p>Dominant families with number of taxa in Binsar Wildlife Sanctuary.</p>
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<p>Dominant genera in Binsar Wildlife Sanctuary.</p>
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<p>Density (individuals ha<sup>−1</sup>) and total basal area (m<sup>2</sup> h<sup>−2</sup>) of trees in BWLS.</p>
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<p>Correlation of tree density with total basal area of tree; tree diversity; shrub density; shrub diversity; tree species richness and concentration of dominance of trees.</p>
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<p>Correlation of biomass and carbon stock: (<b>A</b>) tree diversity; (<b>B</b>) tree density; (<b>C</b>) total basal area; (<b>D</b>) species richness in the BWLS.</p>
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<p>Principal component analysis (PCA) based on different ecological attributes of six forest communities. Abbreviations used: (RS: rainy season; WS: winter season; SS: summer season; TCSeq: total carbon sequestration; SR: species richness; TCS: total carbon stock).</p>
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<p>Map of the study area.</p>
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22 pages, 8042 KiB  
Article
Quercus cerris Leaf Functional Traits to Assess Urban Forest Health Status for Expeditious Analysis in a Mediterranean European Context
by Luca Quaranta, Piera Di Marzio and Paola Fortini
Plants 2025, 14(2), 285; https://doi.org/10.3390/plants14020285 - 20 Jan 2025
Viewed by 175
Abstract
In the Mediterranean basin, urban forests are widely recognized as essential landscape components, playing a key role in nature-based solutions by enhancing environmental quality and providing a range of ecosystem services. The selection of woody plant species for afforestation and reforestation should prioritize [...] Read more.
In the Mediterranean basin, urban forests are widely recognized as essential landscape components, playing a key role in nature-based solutions by enhancing environmental quality and providing a range of ecosystem services. The selection of woody plant species for afforestation and reforestation should prioritize native species that align with the biogeographical and ecological characteristics of the planting sites. Among these, Quercus cerris L. (Turkey oak) is considered a promising candidate for urban reforestation. However, its fitness within urban forest environments remains poorly understood. This study aimed to identify suitable leaf functional traits for assessing the response of Q. cerris in urban forests and to analyze the main climatic variables influencing its performance in urban contexts. We also proposed practical, rapid monitoring tools to compare urban and natural forests across different seasons. The results demonstrated that Q. cerris experiences significant water stress in urban forests due to the combined effects of drought and high temperatures. To find the tools to mitigate this stress, the differences between leaf traits such as specific leaf area, thickness, and the contents of chlorophyll, anthocyanins, and flavonols in urban and natural forests were analyzed. Our findings underscore the high adaptability of Q. cerris to varied climatic and environmental conditions. This study provides a practical method for rapidly assessing the responses of tree species to climate change. In the future, this approach will be tested on other native species that are characteristic of Mediterranean forest ecosystems to help with choosing afforestation and reforestation strategies. Full article
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Figure 1
<p>Kiviat diagram showing the weighted values of EIV 1.0 indexes (with an adimensional range value of 0 to 10) for the three stands (UF = urban forest; PUF = peri-urban forest; and NF = natural forest).</p>
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<p>Correlation matrix showing the results of Pearson’s correlation analysis, which was performed on the entire dataset (11 variables; three stands; three time sampling). Pearson correlation coefficient values and directions are displayed with the following rule: positive correlation from white to blue and negative correlation from white to red on the color scale. Boxes are marked gray when <span class="html-italic">p</span> &lt; 0.05. The inclination of the ellipse is representative of the positivity or negativity of the correlation, while its smaller or larger range indicates the intensity of the correlation. SLA = specific leaf area; LDMC = leaf dry matter content; THICK_M = leaf thickness; Flv_M = flavonol content; CHL_M = chlorophyll content; Anth_M = anthocyanin content; LAI = leaf area index; LST = land surface temperature; PPT = precipitation; SMOI = soil moisture; and ACTEVP = actual evapotranspiration.</p>
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<p>The correlation matrix shows the results of Pearson’s correlation analysis, which was performed separately on (<b>a</b>) UF—urban forest, (<b>b</b>) PUF—peri-urban forest, and (<b>c</b>) NF—natural forest stands. Pearson’s correlation coefficient values and directions are displayed with the following rule: positive correlation from white to blue and negative correlation from white to red on the color scale. Boxes are marked gray when <span class="html-italic">p</span> &lt; 0.05. The inclination of the ellipse is representative of the positivity or negativity of the correlation, while its smaller or larger range indicates the intensity of the correlation. SLA = specific leaf area; LDMC = leaf dry matter content; THICK_M = leaf thickness; Flv_M = flavonol content; CHL_M = chlorophyll content; Anth_M = anthocyanin content; LAI = leaf area index; LST = land surface temperature; PPT = precipitation; SMOI = soil moisture; and ACTEVP = actual evapotranspiration.</p>
Full article ">Figure 3 Cont.
<p>The correlation matrix shows the results of Pearson’s correlation analysis, which was performed separately on (<b>a</b>) UF—urban forest, (<b>b</b>) PUF—peri-urban forest, and (<b>c</b>) NF—natural forest stands. Pearson’s correlation coefficient values and directions are displayed with the following rule: positive correlation from white to blue and negative correlation from white to red on the color scale. Boxes are marked gray when <span class="html-italic">p</span> &lt; 0.05. The inclination of the ellipse is representative of the positivity or negativity of the correlation, while its smaller or larger range indicates the intensity of the correlation. SLA = specific leaf area; LDMC = leaf dry matter content; THICK_M = leaf thickness; Flv_M = flavonol content; CHL_M = chlorophyll content; Anth_M = anthocyanin content; LAI = leaf area index; LST = land surface temperature; PPT = precipitation; SMOI = soil moisture; and ACTEVP = actual evapotranspiration.</p>
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<p>Principal component analysis scree plot of the eigenvalues (blue) with “broken stick” (red: eigenvalues expected under a random model), in which it is shown that the first two components explain more than 64% of the variance.</p>
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<p>Scatter plot of the principal component analysis biplot depicting the relationship between the variables and the three stands. Urban forest (circle), peri-urban forest (X symbol), and natural forest (square) in three sampling times (June—green; July—red; September—blue). SLA = specific leaf area; LDMC = leaf dry matter content; THICK_M = leaf thickness; Flv_M = flavonol content; CHL_M = chlorophyll content; Anth_M = anthocyanin content; LAI = leaf area index; LST = land surface temperature; PPT = precipitation, SMOI = soil moisture; and ACTEVP = actual evapotranspiration.</p>
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<p>Two-way ANOVA box plots (a Tukey post hoc analysis was used to test statistical significance: ns = not significant, · = <span class="html-italic">p</span> &lt; 0.1, * = <span class="html-italic">p</span> &lt; 0.05, ** = <span class="html-italic">p</span> &lt; 0.01, *** = <span class="html-italic">p</span> &lt; 0.001) that describe the trends of the three stands (green—natural forest; yellow—peri-urban forest; and red—urban forest) in three periods (from left to right: Jun = June, Jul = July, and Sep = September). (<b>a</b>) Specific leaf area (SLA). (<b>b</b>) Leaf dry matter content (LDMC).</p>
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<p>Two-way ANOVA box plots (a Tukey HSD post hoc analysis was used to test statistical significance: ns = not significant, · = <span class="html-italic">p</span> &lt; 0.1, * = <span class="html-italic">p</span> &lt; 0.05, *** = <span class="html-italic">p</span> &lt; 0.001) that describe the trends of the three stands (green—natural forest; yellow—peri-urban forest; and red—urban forest) in three periods (from left to right: Jun = June, Jul = July, and Sep = September). (<b>a</b>) Leaf thickness (THICK_M). (<b>b</b>) Chlorophyll content (CHL_M).</p>
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<p>Two-way ANOVA box plots (a Tukey post hoc analysis was used to test statistical significance: ns = not significant, · = <span class="html-italic">p</span> &lt; 0.1, *** = <span class="html-italic">p</span> &lt; 0.001) that describe the trends of the three stands (green—natural forest; yellow—peri-urban forest; and red—urban forest) in three periods (from left to right: Jun = June, Jul = July, and Sep = September). (<b>a</b>) Flavonol content (Flv_M). (<b>b</b>) Anthocyanin content (Anth_M).</p>
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<p>Land surface temperature (LST) maps of the Campobasso municipality (<a href="https://app.climateengine.org/climateEngine" target="_blank">https://app.climateengine.org/climateEngine</a> (accessed on 1 August 2024)), representing the mean temperature of the two months before each sampling date: (<b>a</b>) April–May for the June sampling; (<b>b</b>) May–June for the July sampling; and (<b>c</b>) July–August for the September sampling. NF—natural forest; PUF—peri-urban forest; and UF—urban forests.</p>
Full article ">Figure 9 Cont.
<p>Land surface temperature (LST) maps of the Campobasso municipality (<a href="https://app.climateengine.org/climateEngine" target="_blank">https://app.climateengine.org/climateEngine</a> (accessed on 1 August 2024)), representing the mean temperature of the two months before each sampling date: (<b>a</b>) April–May for the June sampling; (<b>b</b>) May–June for the July sampling; and (<b>c</b>) July–August for the September sampling. NF—natural forest; PUF—peri-urban forest; and UF—urban forests.</p>
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<p>Location of the three stands, urban forest (UF), peri-urban forest (PUF), natural forest (NF), in the Campobasso municipality, and the location of the Molise region in Italy (red color).</p>
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15 pages, 9308 KiB  
Article
Climate Change Drives the Adaptive Distribution and Habitat Fragmentation of Betula albosinensis Forests in China
by Huayong Zhang, Yue Zhou, Xiande Ji, Zhongyu Wang and Zhao Liu
Forests 2025, 16(1), 184; https://doi.org/10.3390/f16010184 - 19 Jan 2025
Viewed by 392
Abstract
Betula albosinensis serves as an important constructive and afforestation tree species in mountainous areas. Its suitable habitat and habitat quality are highly vulnerable to the climate. However, few studies have centered on the shrinkage, expansion, and habitat fragmentation of B. albosinensis forests under [...] Read more.
Betula albosinensis serves as an important constructive and afforestation tree species in mountainous areas. Its suitable habitat and habitat quality are highly vulnerable to the climate. However, few studies have centered on the shrinkage, expansion, and habitat fragmentation of B. albosinensis forests under climate change. In this study, the Random Forest model was employed to predict current and future trends of shrinking and expanding of B. albosinensis, while a composite landscape index was utilized to evaluate the habitat fragmentation in the highly suitable habitats of B. albosinensis. The results indicated that suitable habitats for B. albosinensis were primarily concentrated in the vicinities of the Qinling, Qilian, and Hengduan Mountains, situated in western China. The most influential factor affecting the distribution of B. albosinensis was temperature seasonality (Bio4). In future scenarios, the center of distribution of B. albosinensis was projected to shift towards the west and higher altitudes. The total suitable habitats of B. albosinensis were anticipated to expand under the scenarios of SSP370 and SSP585 in the 2090s, while they were expected to contract under the remaining scenarios. Although these results indicated that the suitable areas of habitat for B. albosinensis were relatively intact on the whole, fragmentation increased with climate change, with the highest degree of fragmentation observed under the SSP585 scenario in the 2090s. The findings of this study provide a foundation for the protection of montane vegetation, the maintenance of montane biodiversity, and the evaluation of species’ habitat fragmentation. Full article
(This article belongs to the Section Forest Ecology and Management)
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<p>The contribution rate of environmental variables in the RF model.</p>
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<p>Potential suitable habitat of <span class="html-italic">B. albosinensis</span> under the current climate in China.</p>
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<p>Distribution of <span class="html-italic">B. albosinensis</span> forests under the SSP126 (<b>a</b>,<b>d</b>), SSP370 (<b>b</b>,<b>e</b>), and SSP585 (<b>c</b>,<b>f</b>) scenarios in the 2050s (<b>a</b>–<b>c</b>) and 2090s (<b>d</b>–<b>f</b>) in China.</p>
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<p>Shrinkage and expansion of <span class="html-italic">B. albosinensis’s</span> suitable habitat in the 2050s (<b>a</b>) and 2090s (<b>b</b>).</p>
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<p>Spatial distribution of fragmentation in highly suitable habitats of <span class="html-italic">B. albosinensis</span> under current climate in China.</p>
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<p>Spatial distribution of fragmentation in highly suitable habitat of <span class="html-italic">B. albosinensis</span> under the SSP126 (<b>a</b>,<b>d</b>), SSP370 (<b>b</b>,<b>e</b>), and SSP585 (<b>c</b>,<b>f</b>) scenarios in the 2050s (<b>a</b>–<b>c</b>) and 2090s (<b>d</b>–<b>f</b>) in China.</p>
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<p>Percentage of fragmentation at each level under different scenarios.</p>
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18 pages, 5849 KiB  
Article
Growth, Productivity, and Nutrient Return of a Mixed Plantation of Fast-Growing Eucalyptus Hybrid and Acacia auriculiformis Trees in Thailand
by Jetsada Wongprom, Narinthorn Jumwong, Pattama Sangvisitpirom, Sapit Diloksumpun and La-ongdao Thaopimai
Forests 2025, 16(1), 182; https://doi.org/10.3390/f16010182 - 19 Jan 2025
Viewed by 291
Abstract
Mixed-species plantations involving Eucalyptus and Acacia trees are an effective alternative for managing sustainable plantations. In this study, we evaluated the growth, productivity, nutrient return, and soil properties of a mixed Eucalyptus hybrid (Eucalyptus camaldulensis Dehnh. × E. urophylla S.T. Blake; E) and [...] Read more.
Mixed-species plantations involving Eucalyptus and Acacia trees are an effective alternative for managing sustainable plantations. In this study, we evaluated the growth, productivity, nutrient return, and soil properties of a mixed Eucalyptus hybrid (Eucalyptus camaldulensis Dehnh. × E. urophylla S.T. Blake; E) and Acacia auriculiformis A. Cunn. ex Benth. plantation (A) and Eucalyptus hybrid and A. auriculiformis plantations. The mixed Eucalyptus hybrid and A. auriculiformis plantation included three ratios at E33:A67, E50:A50, and E67:A33, while the Eucalyptus (E100) and A. auriculiformis (A100) plantations were established on degraded lands in the Had Wanakorn Forestry Research and Student Training Station, Prachuap Khiri Khan province, Thailand. Three replications within a plot size of 20 × 20 m2 were designed to plant Eucalyptus hybrid and A. auriculiformis seedlings at a spacing of 2 × 3 m2. The diameters at breast height (DBH) and height (H) of the Eucalyptus hybrid and A. auriculiformis were measured and monitored after planting for five years. The aboveground biomass of the five-year-old mixed and monoculture plantations was then estimated. Litterfall production and nutrient return from the mixed and monoculture plantations were measured for three years. In addition, soil samples at depths of 0–5, 5–10, and 10–20 cm were collected to analyze the soil’s chemical properties. Differences in growth, aboveground biomass, litterfall production, nutrient return, and soil properties were analyzed and tested using Tukey’s HSD. The results indicated that both the DBH and H of the Eucalyptus hybrid in the mixed and monoculture plantations were not significantly different (p > 0.05). Similarly, the DBH and H of A. auriculiformis in each treatment were also not significantly different (p > 0.05). However, the DBH and H of the Eucalyptus hybrid were higher than those of A. auriculiformis. The aboveground biomass for the mixed plantation ratios E50:A50, E100, E67:A33, and E33:A67 was not significantly different, while the stem biomass was the highest in E100. Litterfall production was influenced by the proportion of the Eucalyptus hybrid relative to A. auriculiformis, but the monoculture A100 plantation had the highest litter production. The nitrogen return estimated for the mixed plantation was between A100 and E100. Similarly, the total nitrogen in the topsoil (0–5 cm) of the mixed plantation was higher than that in the monoculture E100 plantation. These results indicate that mixing A. auriculiformis with Eucalyptus can improve soil nutrients and nutrient cycling and increase nutrient returns, suggesting that mixed plantations are an effective option for sustainable plantation management and can mitigate the negative environmental impacts of Eucalyptus monocultures. Full article
(This article belongs to the Special Issue Forest Stand and Biomass Management)
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<p>Location of study site at Had Wanakorn Forestry Research and Student Training Station, Thap Sakae district, Prachuap Khiri Khan province, Thailand.</p>
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<p>The layout of the <span class="html-italic">Eucalyptus</span> hybrid (<span class="html-fig-inline" id="forests-16-00182-i001"><img alt="Forests 16 00182 i001" src="/forests/forests-16-00182/article_deploy/html/images/forests-16-00182-i001.png"/></span>) and <span class="html-italic">Acacia auriculiformis</span> (<span class="html-fig-inline" id="forests-16-00182-i002"><img alt="Forests 16 00182 i002" src="/forests/forests-16-00182/article_deploy/html/images/forests-16-00182-i002.png"/></span>) in the mixed-species and monoculture plantations, with the location of litter traps (<span class="html-fig-inline" id="forests-16-00182-i003"><img alt="Forests 16 00182 i003" src="/forests/forests-16-00182/article_deploy/html/images/forests-16-00182-i003.png"/></span>), at the ratios A100, E100, E67:A33, E50:A50, and E33:A67 at the Had Wanakorn Forestry Research and Student Training Station, Thap Sakae district, Prachuap Khiri Khan province, Thailand.</p>
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<p>DBH (<b>A</b>) and H (<b>B</b>) of the 1–5-year-old <span class="html-italic">Eucalyptus</span> hybrid (E) and <span class="html-italic">A. auriculiformis</span> (A) in the mixed and monoculture plantations.</p>
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<p>Stem biomass (<b>A</b>) and aboveground biomass (<b>B</b>) of the 5-year-old <span class="html-italic">Eucalyptus</span> hybrid and <span class="html-italic">A. auriculiformis</span> in the mixed and monoculture plantations. The letters (a, b, c, and d) above the bars indicate statistical differences at <span class="html-italic">p</span> &lt; 0.05, as determined by Tukey’s HSD.</p>
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<p>Monthly litterfall of the <span class="html-italic">Eucalyptus</span> hybrid and <span class="html-italic">A. auriculiformis</span> in the mixed and monoculture plantations from February 2021 to January 2024.</p>
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<p>Litterfall separated by components, including leaves, branches, barks, reproductive parts, and miscellaneous parts, of the <span class="html-italic">Eucalyptus</span> hybrid and <span class="html-italic">A. auriculiformis</span> at ages of 3.5 (<b>A</b>), 4.5 (<b>B</b>), and 5.5 years (<b>C</b>). The mean litterfall (<b>D</b>) estimated for the mixed and monoculture plantations. The letters (a, b, c, and d) above the bars indicate statistical differences at <span class="html-italic">p</span> &lt; 0.05, as determined by Tukey’s HSD.</p>
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15 pages, 2185 KiB  
Article
The Short-Term Impact of Logging Intensity on the Stand State of Middle-Aged Masson Pine (Pinus massoniana Lamb.) Plantations
by Jing Tu, Zhongwen Zhao and Zongzheng Chai
Forests 2025, 16(1), 183; https://doi.org/10.3390/f16010183 - 19 Jan 2025
Viewed by 242
Abstract
By assessing the short-term impact that various logging intensities have on stand state in middle-aged P. massoniana plantations, this investigation aimed to establish a theoretical foundation to support the judicious management of Pinus massoniana plantations. Five distinct logging intensity categories were delineated (0%, [...] Read more.
By assessing the short-term impact that various logging intensities have on stand state in middle-aged P. massoniana plantations, this investigation aimed to establish a theoretical foundation to support the judicious management of Pinus massoniana plantations. Five distinct logging intensity categories were delineated (0%, 10%, 20%, 30%, 40%). To construct a robust stand-state evaluation framework, nine representative indicators across the three dimensions of structure, vitality, and diversity were selected. We scrutinized the short-term impacts of logging intensity by employing the unit circle method. The findings revealed that (1) four indicators—stand density, tree health, species composition, and species diversity—exhibited pronounced sensitivity to logging intensity. These four exhibited significant improvements in the short-term post-logging (p < 0.05). Conversely, the indicators of species evenness, diameter distribution, height distribution, tree dominance, and stand growth exhibited a more subdued response to logging intensity. These five necessitated an extended period to begin to improve. (2) The comprehensive evaluation values measuring the stand state of middle-aged P. massoniana plantations initially ascended but then subsequently descended as logging intensity escalated. The stand-state zenith was pinpointed at an approximate 30% logging intensity. (3) A highly significant linear correlation emerged between the unit circle method results and the principal component analysis results in evaluating stand state (R2 = 0.909, p < 0.001), and the unit circle method proved to be more intuitive and responsive. In summation, logging intensity exerted a substantial influence on stand state in middle-aged P. massoniana plantations, with moderate logging (circa 30% logging intensity) enhancing stand state the most. The unit circle method proficiently and effectively illuminated the short-term effects of logging intensity on the stand dynamics of middle-aged P. massoniana plantations, so it thereby may provide invaluable guidance for the formulation of specific forest management strategies. Full article
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<p>Geographical location of and sample block distribution in the study area.</p>
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<p>Unit circle method stand-state evaluation of <span class="html-italic">Masson pine</span> mid-aged plantations. The differently colored sectors represent various stand state indicators. The area of the sector that is colored in represents the magnitude of each stand state indicator value, with a larger area signifying a better indicator. The symbol ω in the upper right corner represents the value of the comprehensive evaluation of each forest stand state.</p>
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<p>Principal component analysis-based stand-state evaluation of <span class="html-italic">Masson pine</span> mid-aged plantations. (<b>a</b>) Based on the principal component analysis, the load values of stand state indicators; Different colored boxes represent different logging intensity sample areas; (<b>b</b>) based on the principal component analysis, the ranking of stand state indicator weights.</p>
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<p>Correlation analysis of unit circle method versus principal component analysis stand-state evaluation results.</p>
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19 pages, 588 KiB  
Article
Natural Hybridization Between Quercus crassipes and Q. crassifolia (Fagaceae) Is a Key Process to Ensure the Biodiversity of Their Associated Lichen Community
by Leticia Valencia-Cuevas, Jennie Melhado-Carboney and Efraín Tovar-Sánchez
Diversity 2025, 17(1), 69; https://doi.org/10.3390/d17010069 - 19 Jan 2025
Viewed by 338
Abstract
Lichens are organisms whose dynamics take place on terrestrial substrates such as rock, dead wood, living plants, and soil. Living trees are used for lichens as structural support to access light. However, little is known about how the genetic traits of a host [...] Read more.
Lichens are organisms whose dynamics take place on terrestrial substrates such as rock, dead wood, living plants, and soil. Living trees are used for lichens as structural support to access light. However, little is known about how the genetic traits of a host tree influence which lichen species grow on it and, consequently, the community structure of this funga. In this study, we investigated how the genetic diversity GD of host oak taxa (Quercus crassifolia, Q. crassipes and their putative hybrid: Q. × dysophylla) influence the community structure of the associated epiphytic lichen community in two hybrid zones (HZs) in Central Mexico. The lichen community was composed of 76 species, 27 genera and 14 families. We found significant differences in lichen composition between genetically distinct individuals and oak taxa in each HZ. Lichen diversity in Q. × dysophylla was intermediate and significantly different between parents in both HZs. We conclude that genetic differences between host oaks promoted significantly different lichen communities and that hybrids may act as ecological islands, accumulating lichen species from both parental species and their own novel species. Consequently, the conservation of HZs due to their high GD may be a strategy to ensure biodiversity conservation of oak-associated lichen communities. Full article
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<p>Lichen community composition differences among host oak genotypes (<span class="html-italic">Quercus crassifolia</span>, <span class="html-italic">Q</span>. × <span class="html-italic">dysophilla, and Q. crassipes</span>) in two hybrid zones using nonmetric multidimensional scaling (NMDS). Each point is a two-dimensional (axis 1 and axis 2) representation of the lichen species composition (10 points per host oak genotype). Distances between points reflect a dissimilarity matrix created using the Bray–Curtis dissimilarity coefficient (Faith et al., 1987 [<a href="#B52-diversity-17-00069" class="html-bibr">52</a>]). Points that are close together have lichen communities that are more similar in composition compared to points that are far apart. Data of Canalejas hybrid zone (Stress values: 0.149. Final instability, 0.0001) and Tlaxco hybrid zone (stress values of 0.128 and final instability of 0.0001) were used in this analysis.</p>
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12 pages, 639 KiB  
Article
Comparison of Fecundity and Gall-Forming of the Horned-Gall Aphid, Schlechtendalia chinensis (Hemiptera: Aphididae) from Different Populations
by Xin Xu, Zhaohui Shi, Chang Tong, Shuxia Shao, Hongyuan Wei and Zixiang Yang
Insects 2025, 16(1), 100; https://doi.org/10.3390/insects16010100 - 18 Jan 2025
Viewed by 317
Abstract
The horned-gall aphid, Schlechtendalia chinensis, is the most economically valuable Chinese gallnut aphid species, playing a decisive role in the production of Chinese gallnuts. The method of cultivating the gallnut species with artificial moss and increasing the yield of gallnuts after inoculation [...] Read more.
The horned-gall aphid, Schlechtendalia chinensis, is the most economically valuable Chinese gallnut aphid species, playing a decisive role in the production of Chinese gallnuts. The method of cultivating the gallnut species with artificial moss and increasing the yield of gallnuts after inoculation has been applied in the main producing areas of Chinese gallnuts. However, it is still unclear whether artificial cultivation affects the fecundity and gall-forming effect of S. chinensis. In this study, autumn migrant aphids of S. chinensis from wild, artificial and introduced populations were used as materials to cultivate and inoculate under the same environment. The number of male and female sexuales, fundatrices, the galls per tree, and the total weight of galls per tree in subsequent generations were analyzed, and differences in the fecundity and gall-forming effects of different populations were analyzed. The results showed that the fecundity of the wild population was stronger than that of the artificial population, and the number of aphids produced by a single spring migrant and the number of fundatrices increased by 75.86% and 81.62%, respectively. Compared with the introduced population, the survival rate of female sexuales in the local population was higher. Compared with the artificial population, the gall-forming effect of the wild population was better; the number of galls per tree, the weight of single gall, and the total weight of galls per tree increased by 68.33%, 50.77%, and 153.78%, respectively; and the gall preservation rate increased significantly. Artificial cultivation of S. chinensis will lead to a decrease in fecundity and gall-forming effect in subsequent generations, showing the degradation of the vitality of S. chinensis. Therefore, it is necessary to improve the effect of artificial cultivation of S. chinensis by adopting technical measures such as wild population or introduction. Full article
(This article belongs to the Section Role of Insects in Human Society)
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<p>The number of spring migrant aphids (<b>a</b>), aphids produced by a single spring migrant (<b>b</b>), male and female sexuales (<b>c</b>), and fundatrices (<b>d</b>) in different populations of <span class="html-italic">Schlechtendalia chinensis</span>. Note: LW represents the local wild population; LA represents the local artificial population; ISZ represents the introduced population in Sangzhi; ISY represents the introduced population in Shanyang; IYY represents the introduced population in Youyang. Data in the figure are mean ± standard error. Those with different lowercase letters on the column indicate that there were significant differences in the numbers of different populations of the aphid (<span class="html-italic">p</span> &lt; 0.05, DMRT method). The same applies below.</p>
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<p>Comparison of the number of fundatrices per plant and the number of galls per plant (<b>a</b>), galls per leaf (<b>b</b>), and compound leaves with galls per branch (<b>c</b>) in different periods of different populations of <span class="html-italic">Schlechtendalia chinensis</span>. Note: LW represents the local wild population; LA represents the local artificial population; ISZ represents the introduced population in Sangzhi; ISY represents the introduced population in Shanyang; IYY represents the introduced population in Youyang. The same uppercase letter on the same group column indicates that the number of the same population in different periods is not significantly different at the 0.05 level (DMRT method). The same lowercase letters on the same type of column indicate that the number of different populations in the same period was not significantly different at the 0.05 level (DMRT method). The same applies below.</p>
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<p>Comparison of the number of fundatrices per plant and the number of galls per plant (<b>a</b>), galls per leaf (<b>b</b>), and compound leaves with galls per branch (<b>c</b>) in different periods of different populations of <span class="html-italic">Schlechtendalia chinensis</span>. Note: LW represents the local wild population; LA represents the local artificial population; ISZ represents the introduced population in Sangzhi; ISY represents the introduced population in Shanyang; IYY represents the introduced population in Youyang. The same uppercase letter on the same group column indicates that the number of the same population in different periods is not significantly different at the 0.05 level (DMRT method). The same lowercase letters on the same type of column indicate that the number of different populations in the same period was not significantly different at the 0.05 level (DMRT method). The same applies below.</p>
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25 pages, 21840 KiB  
Article
A Review of the Psyllid Genus Epipsylla (Hemiptera, Psyllidae) from the Chinese Mainland with Phylogenetic Considerations and the Description of a New Species
by Zhixin He, Daniel Burckhardt, Xinyu Luo, Rongzhen Xu, Wanzhi Cai and Fan Song
Insects 2025, 16(1), 99; https://doi.org/10.3390/insects16010099 (registering DOI) - 18 Jan 2025
Viewed by 233
Abstract
Epipsylla Kuwayama, 1908, constitutes an Old World genus of psyllids with 15 described species. Based on characters of immatures, Epipsylla was recently assigned to Ciriacreminae (Psyllidae). The genus is morphologically well circumscribed but species are currently difficult to identify as many descriptions lack [...] Read more.
Epipsylla Kuwayama, 1908, constitutes an Old World genus of psyllids with 15 described species. Based on characters of immatures, Epipsylla was recently assigned to Ciriacreminae (Psyllidae). The genus is morphologically well circumscribed but species are currently difficult to identify as many descriptions lack detail and precision. Eight species are reported from the Chinese mainland. Here, we provide diagnoses for the adults of these species and, as far as known, the fifth-instar immatures. Figures are provided of taxonomically relevant adult characters. A new species, Epipsylla suni sp. nov., is described from Yunnan (China). We provide illustrations of its habitus and morphological features, and list the host plant. Furthermore, we sequenced the mitochondrial genome of the new species and constructed a phylogenetic tree using thirteen protein-coding genes and two rRNA genes. The results of the molecular phylogenetic analysis using the maximum likelihood method support the assignment to Ciriacreminae. Full article
(This article belongs to the Section Insect Systematics, Phylogeny and Evolution)
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<p>Habitus of <span class="html-italic">Epipsylla suni</span> sp. nov. (<b>A</b>,<b>B</b>) Host plant, <span class="html-italic">Derris taiwaniana</span>; (<b>C</b>,<b>D</b>) adults; (<b>E</b>,<b>F</b>) larvae.</p>
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<p><span class="html-italic">Epipsylla crotalariae</span> Yang &amp; Li, 1984. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus. Scale bar (mm): (<b>A</b>) 0.3; (<b>B</b>) 0.15; (<b>C</b>) 0.1; (<b>D</b>) 0.6; (<b>E</b>) 0.15; (<b>F</b>) 0.15; (<b>G</b>) 0.1; (<b>H</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla guangxiana</span> Yang &amp; Li, 1983. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.25; (<b>B</b>) 0.2; (<b>C</b>) 0.1; (<b>D</b>) 0.5; (<b>E</b>) 0.15; (<b>F</b>) 0.1; (<b>G</b>) 0.1; (<b>H</b>) 0.1; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla hainanana</span> Yang &amp; Li, 1983. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.25; (<b>B</b>) 0.25; (<b>C</b>) 0.1; (<b>D</b>) 0.5; (<b>E</b>) 0.15; (<b>F</b>) 0.12; (<b>G</b>) 0.1; (<b>H</b>) 0.15; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla liui</span> Yang &amp; Li, 1983. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.25; (<b>B</b>) 0.2; (<b>C</b>) 0.1; (<b>D</b>) 0.5; (<b>E</b>) 0.15; (<b>F</b>) 0.12; (<b>G</b>) 0.1; (<b>H</b>) 0.2; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla millettiae</span> Li, Yang &amp; Burckhardt, 2015. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.25; (<b>B</b>) 0.2; (<b>C</b>) 0.1; (<b>D</b>) 0.5; (<b>E</b>) 0.15; (<b>F</b>) 0.12; (<b>G</b>) 0.1; (<b>H</b>) 0.15; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla mucunae</span> Yang &amp; Li, 1984. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.25; (<b>B</b>) 0.15; (<b>C</b>) 0.1; (<b>D</b>) 0.6; (<b>E</b>) 0.15; (<b>F</b>) 0.15; (<b>G</b>) 0.1; (<b>H</b>) 0.15; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla nadana</span> Yang &amp; Li, 1983. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.25; (<b>B</b>) 0.15; (<b>C</b>) 0.1; (<b>D</b>) 0.5; (<b>E</b>) 0.15; (<b>F</b>) 0.12; (<b>G</b>) 0.12; (<b>H</b>) 0.2; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla puerariae</span> Yang &amp; Li, 1983. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.2; (<b>B</b>) 0.15; (<b>C</b>) 0.1; (<b>D</b>) 0.5; (<b>E</b>) 0.18; (<b>F</b>) 0.15; (<b>G</b>) 0.1; (<b>H</b>) 0.12; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla suni</span> Luo, Burckhardt &amp; Cai, sp. nov. (<b>A</b>) Head (antennae removed); (<b>B</b>) female terminalia in lateral view; (<b>C</b>) setae on vein C + Sc; (<b>D</b>) forewing; (<b>E</b>) meracanthus; (<b>F</b>) male terminalia in lateral view (ignoring distal segment of aedeagus and phallobase); (<b>G</b>) inner surface of paramere; (<b>H</b>) distal segment of aedeagus in dorsal view; (<b>I</b>) distal segment of aedeagus in lateral view. Scale bar (mm): (<b>A</b>) 0.25; (<b>B</b>) 0.2; (<b>C</b>) 0.1; (<b>D</b>) 0.5; (<b>E</b>) 0.15; (<b>F</b>) 0.15; (<b>G</b>) 0.12; (<b>H</b>) 0.12; (<b>I</b>) 0.1.</p>
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<p><span class="html-italic">Epipsylla suni</span> Luo, Burckhardt &amp; Cai, sp. nov., fifth-instar immature. (<b>A</b>) Habitus, dorsal aspect on the left half, ventral aspect on the right half; (<b>B</b>) dorsal view of circumanal pore field; (<b>C</b>) ventral view of circumanal pore field; (<b>D</b>) blunt lanceolate seta located in margin of abdomen; (<b>E</b>) tarsal arolium. Scale bar (mm): (<b>A</b>) 0.4; (<b>B</b>) 0.12; (<b>C</b>) 0.12; (<b>D</b>) 0.03; (<b>E</b>) 0.03.</p>
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<p>Habitus of adults. (<b>A</b>,<b>B</b>) <span class="html-italic">E. crotalariae</span>; (<b>C</b>,<b>D</b>) <span class="html-italic">E. guangxiana</span>; (<b>E</b>,<b>F</b>) <span class="html-italic">E. hainanana</span>; (<b>G</b>,<b>H</b>) <span class="html-italic">E. millettiae</span>. (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>) Dorsal view; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>) lateral view. Scale bar: 1 mm.</p>
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<p>Habitus of adults. (<b>A</b>,<b>B</b>) <span class="html-italic">E. mucunae</span>; (<b>C</b>,<b>D</b>) <span class="html-italic">E. nadana</span>; (<b>E</b>,<b>F</b>) <span class="html-italic">E. puerariae</span>; (<b>G</b>,<b>H</b>) <span class="html-italic">E. suni</span>. (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>) Dorsal dorsal view; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>) lateral view. Scale bars: 1 mm.</p>
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<p>Phylogenetic relationship of Psyllidae inferred via IQ-TREE based on mitochondrial genome sequences. Numbers close to the branching points are bootstrap support values.</p>
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13 pages, 3630 KiB  
Article
Genome Sequencing Reveals the Adaptation of Chickens to High Altitudes in Different Regions
by Yizhou Hu, Xing Li, Qixin Guo, Lan Huang, Hao Bai and Guobin Chang
Animals 2025, 15(2), 265; https://doi.org/10.3390/ani15020265 - 18 Jan 2025
Viewed by 216
Abstract
Altitudinal adaptation is a key factor in species formation and leads to increased species diversity. Chickens are one of the most widely distributed and important domesticated species, making them ideal models for studying the evolution of altitudinal adaptation. Therefore, we downloaded and analyzed [...] Read more.
Altitudinal adaptation is a key factor in species formation and leads to increased species diversity. Chickens are one of the most widely distributed and important domesticated species, making them ideal models for studying the evolution of altitudinal adaptation. Therefore, we downloaded and analyzed the total genome data of 160 individual chickens from seven sampling regions at two different altitudes (>3000 m and <600 m). In total, 21,672,487 high-quality single-nucleotide polymorphisms were selected and used for subsequent analyses. First, we interpreted the genetic relationships among chickens from different sampling regions using a neighbor-joining tree, population structure, and four dimensionality reduction methods. We found that 38 genes were significantly associated with altitudinal adaptations by FST and θπ. Functional annotation of the genes showed that they are primarily involved in energy metabolism, ion channel activity, and blood pressure regulation. Our results provide evidence of genetic diversity among different chicken breeds and reveal the mechanisms of adaptation to high altitudes. Full article
(This article belongs to the Section Animal Genetics and Genomics)
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<p>Group structure analysis. (<b>a</b>) NJ tree; (<b>b</b>) principal component analysis; (<b>c</b>) population structure analysis.</p>
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<p>Two-dimensional visualization of population genotype data by four different downscaling methods. (<b>a</b>) UMAP dimensionality reduction method; (<b>b</b>) t-SNE dimensionality reduction method; (<b>c</b>) PCA-tSNE dimensionality reduction method; (<b>d</b>) PCA-UMAP dimensionality reduction method.</p>
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<p>Population genetic evolution analysis of local chicken breeds. (<b>a</b>) <span class="html-italic">F<sub>ST</sub></span> and <span class="html-italic">π</span> values between pairwise local chicken breeds; The values under the shadow represent <span class="html-italic">F<sub>ST</sub></span> values, while the values connected by lines between pairs represent π values; (<b>b</b>) Linkage disequilibrium decay analysis. (<b>c</b>) Gene flow analysis; (<b>d</b>) Distribution of ROH fragment lengths and quantities in different local chicken breeds; (<b>e</b>) Number of ROH fragments in different length intervals; (<b>f</b>) Proportion of ROHs in different length ranges among various local chicken breeds.</p>
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<p>Genome-wide selective analysis of local chickens. (<b>a</b>) Selective analysis of high-altitude and low-altitude local chickens using <span class="html-italic">F<sub>ST</sub></span> and <span class="html-italic">π-Ratio</span>; (<b>b</b>) Gene Ontology (GO) annotation of candidate genes (showing only 30 terms) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The left panel shows GO annotation, and the right panel shows KEGG enrichment analysis.</p>
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19 pages, 3640 KiB  
Article
Changes in the Timing of Autumn Leaf Senescence of Maple and Ginkgo Trees in South Korea over the Past 30 Years: A Comparative Assessment of Process-Based, Linear Regression, and Machine-Learning Models
by Sukyung Kim, Minkyu Moon and Hyun Seok Kim
Forests 2025, 16(1), 174; https://doi.org/10.3390/f16010174 - 17 Jan 2025
Viewed by 298
Abstract
Changes in vegetation activities driven by climate change serve as both a sensitive indicator and a key driver of climate impacts, underscoring the need for accurate phenological predictions. Delays in leaf senescence due to rising air temperatures increase the risk of damage from [...] Read more.
Changes in vegetation activities driven by climate change serve as both a sensitive indicator and a key driver of climate impacts, underscoring the need for accurate phenological predictions. Delays in leaf senescence due to rising air temperatures increase the risk of damage from early frost, potentially affecting growth and survival in subsequent years. This study aimed to quantify long-term changes in leaf senescence timing for palmate maple and ginkgo trees, explore their associations with environmental factors, and compare the performance of multiple modeling approaches to identify their strengths and limitations for phenological predictions. Using data from 48 sites across South Korea (1989–2020), this study analyzed trends in the timing of leaf senescence for maple and ginkgo trees and compared the performance of process-based models (CDD_T, CDD_P, TP_T, TP_P), a linear regression model, and machine-learning models (random forest, RF; gradient-boosting decision tree, GBTD). Leaf senescence timing for both species has progressively been delayed, with ginkgo trees showing a faster rate of change (0.20 vs. 0.17 days per year, p < 0.05). Delayed senescence was observed in most regions (81% for maple and 75% for ginkgo), with statistically significant delays (p < 0.05) at half of the sites. Machine-learning models demonstrated the highest training accuracy (RMSE < 4.0 days, r > 0.90). Evaluation with independent datasets revealed that the RF and process-based TP_P (including minimum temperature and photoperiod) using a site-specific approach performed best (RMSE < 5.5 days, r > 0.75). Key environmental factors identified by RF included autumn minimum or mean temperatures and a summer photoperiod. By conducting this comparative assessment, the study provides insights into the applicability of different modeling approaches for phenology research and highlights their implications for vegetation management and climate change adaptation. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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<p>Observation site locations. The map illustrates 48 sites where autumn phenological events of palmate maple (<span class="html-italic">Acer</span> spp.) and ginkgo (<span class="html-italic">Ginkgo biloba</span>) trees were observed. Data from 16 sites (marked with red-outlined circles), which have been continuously monitored from 1989 to 2020, were used for a Mann–Kendall trend analysis to assess changes in the timing of autumn leaf senescence.</p>
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<p>(<b>a</b>) Changes in the mean autumn leaf senescence timing [<math display="inline"><semantics> <mrow> <mi mathvariant="normal">d</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">s</mi> <mo> </mo> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>] for palmate maple (Acer; Acer spp.) and ginkgo (Ginkgo; Ginkgo biloba) trees over all sites from 1989 to 2020, (<b>b</b>) inter-site variation in leaf senescence timing [<math display="inline"><semantics> <mrow> <mi mathvariant="normal">d</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">s</mi> <mo> </mo> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>], (<b>c</b>) changes in the autumn temperatures [°C <math display="inline"><semantics> <mrow> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>] over all sites from 1989 to 2020, and (<b>d</b>) inter-site variation in autumn temperatures [°C <math display="inline"><semantics> <mrow> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>]. Inter-site variation indicates the standard deviation among all sites, and the <span class="html-italic">p</span>-values represent the statistical significance of the trends, as determined by the Mann–Kendall test. LS: leaf senescence timing, AT: autumn temperatures (mean values of T_max, T_avg, and T_min from September to November), DOY: day of year, T_max: daily maximum temperature, T_avg: daily average temperature, T_min: daily minimum temperature.</p>
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<p>Rate of change in leaf senescence timing [<math display="inline"><semantics> <mrow> <mi mathvariant="normal">d</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">s</mi> <mo> </mo> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>] for (<b>a</b>) palmate maple (<span class="html-italic">Acer</span> spp.) and (<b>b</b>) ginkgo (<span class="html-italic">Ginkgo biloba</span>) trees at each site from 1989 to 2020. The color of the points represents the average onset date of leaf coloring over the study period at each site [<math display="inline"><semantics> <mrow> <mi mathvariant="normal">d</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">y</mi> <mo> </mo> <mi mathvariant="normal">o</mi> <mi mathvariant="normal">f</mi> <mo> </mo> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> </semantics></math>], and larger points indicate a statistically significant trend, as determined by the Mann–Kendall test (<math display="inline"><semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.05</mn> </mrow> </semantics></math>).</p>
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<p>Box plots showing the distribution of RMSE calculated for each site (RMSE<sub>site</sub>) for (<b>a</b>) palmate maple (<span class="html-italic">Acer</span> spp.) and (<b>b</b>) ginkgo (<span class="html-italic">Ginkgo biloba</span>) trees, grouped by modeling approach (multi-site: blue boxes, site-specific: red boxes) and model type (GBDT, RF, LR, TP_P, TP_T, CDD_P, CDD_T). Each panel presents results for the training set (left) and validation set (right). Different letters and bold-outlined boxes indicate significant differences in RMSE<sub>site</sub> among model types and between modeling approaches, respectively (<span class="html-italic">p</span> &lt; 0.05). Letter colors denote the modeling approach (blue: multi-site, red: site-specific), and the absence of letters indicates no significant differences.</p>
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<p>Permutation importance of predictors for leaf senescence timing in (<b>a</b>) palmate maple (<span class="html-italic">Acer</span> spp.) and (<b>b</b>) ginkgo (<span class="html-italic">Ginkgo biloba</span>) trees based on a random forest model constructed by integrating all sites.</p>
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<p>Rate of change in autumn temperatures at each site [°C <math display="inline"><semantics> <mrow> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>] during (<b>a</b>) 1989–2010 and (<b>b</b>) 2011–2020. Rate of change in leaf senescence timing [<math display="inline"><semantics> <mrow> <mi mathvariant="normal">d</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">s</mi> <mo> </mo> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>] for palmate maple (Acer; <span class="html-italic">Acer</span> spp.) and ginkgo (Ginkgo; <span class="html-italic">Ginkgo biloba</span>) at each site [<math display="inline"><semantics> <mrow> <mi mathvariant="normal">d</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">s</mi> <mo> </mo> <msup> <mrow> <mi mathvariant="normal">y</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>] during (<b>c</b>) 1989–2010 and (<b>d</b>) 2011–2020, plotted against the average timing of leaf senescence at each site. Autumn temperatures (AT) represent the mean values of T_avg and T_min from September to November), and leaf senescence (LS) timing represents the onset date of leaf coloring. T_avg: daily mean temperature, T_min: daily minimum temperature.</p>
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14 pages, 1704 KiB  
Article
Lignin Metabolism Is Crucial in the Plant Responses to Tambocerus elongatus (Shen) in Camellia sinensis L.
by Wenli Wang, Xiaogui Zhou, Qiang Hu, Qiuhong Wang, Yanjun Zhou, Jingbo Yu, Shibei Ge, Lan Zhang, Huawei Guo, Meijun Tang and Xin Li
Plants 2025, 14(2), 260; https://doi.org/10.3390/plants14020260 - 17 Jan 2025
Viewed by 310
Abstract
Tambocerus elongatus (Shen) (Hemiptera: Cicadellidae) is a devastating insect pest species of Camellia sinensis, significantly affecting the yield and quality of tea. Due to growing concerns over the irrational use of insecticides and associated food safety, it is crucial to better understand [...] Read more.
Tambocerus elongatus (Shen) (Hemiptera: Cicadellidae) is a devastating insect pest species of Camellia sinensis, significantly affecting the yield and quality of tea. Due to growing concerns over the irrational use of insecticides and associated food safety, it is crucial to better understand the innate resistance mechanism of tea trees to T. elongatus. This study aims to explore the responses of tea trees to different levels of T. elongatus infestation. We first focused on the primary metabolism and found that the amino acid levels decreased significantly with increasing T. elongatus infestation, while sugar accumulation showed an opposite trend. Moreover, secondary metabolite analysis showed a significant increase in flavonoid compounds and lignin content after T. elongatus infestation. Metabolomics analysis of the flavonoid compounds revealed a decrease in the proanthocyanidin level and an increase in anthocyanidin glycosides (anthocyanins and their derivatives) after T. elongatus infestation. T. elongatus infestation also caused a decrease in the abundance of non-ester catechins and an increase in the abundance of ester catechins. Furthermore, the gene expression analysis revealed that transcripts of genes involved in flavonoid biosynthesis, such as CsCHI, CsF3H, CsF3′H, CsFNS, CsFLS, and CsUFGT, were down-regulated, while genes involved in the lignin pathway were up-regulated by insect infestation, suggesting that lignin probably plays a pivotal role in tea plant response to T. elongatus infestation. Analysis of the expression of related genes indicates that the jasmonate (JA) pathway primarily responds to leafhopper damage. These findings suggest that the lignin pathway and JA play a preferential role in tea plant response to T. elongatus. Furthermore, the production of saccharides and the accumulation of anthocyanin glycosides in the flavonoid metabolic pathway are critical during this stress response. Further exploration of the roles of anthocyanin glycosides and lignin in tea tree resistance could provide a theoretical basis for understanding the defense mechanism of tea trees against T. elongatus damage. Full article
(This article belongs to the Special Issue Sustainable Strategies for Tea Crops Protection)
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<p><span class="html-italic">T. elongatus</span> feeding affects the abundance of major amino acids and sugars in tea leaves. Relative abundance of (<b>a</b>). Theanine; (<b>b</b>). Arginine; (<b>c</b>). Aspartic acid; (<b>d</b>). Glutamic acid; and (<b>e</b>). Major sugars in tea buds. The color gradient from red to blue indicates the abundance of sugars from high to low. CK: control, no larval infestation; MD: moderate infestation level, 5 larvae per bud; SD: severe infestation level, 10 larvae per bud. The relative abundance of various amino acids was determined based on the peak areas from the metabolomics results. The mean denoted by the different lower-case letters indicates statistically significant differences between the treatments according to Duncan’s Multiple Range Test (DMRT) at <span class="html-italic">p</span> &lt; 0.05, where ns represents non-significant and error bars indicate standard deviation.</p>
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<p>Flavonoid, total lignin, and flavonoid-targeted metabolite contents in different infestation levels of <span class="html-italic">T. elongatus</span>. (<b>a</b>). Content of total flavonoids. (<b>b</b>). Content of total lignin. (<b>c</b>). Abundance of Proanthocyanidin. (<b>d</b>). Abundance of anthocyanins and their glycosides. (<b>e</b>). Abundance of the main catechins. CK: control, no larval infestation; MD: moderate infestation level, 5 larvae per bud; SD: severe infestation level, 10 larvae per bud. The color gradient from red to blue indicates the abundance from high to low. The data denoted by the different lower-case letters indicated significant differences between the treatments (DMRT, <span class="html-italic">p</span> &lt; 0.05) and error bars indicate standard deviation. The content values are based on the dry weight of tea leaves.</p>
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<p>Expression of genes involved in the phenylpropanoid metabolic pathway. PAL, Phenylalanine ammonia-lyase; C4H, Cinnamic acid 4-hydroxylase; 4CL, 4-Coumarinyl-CoA ligase; CHS, Chalcone synthase; CHI, Chalcone isomerase; F3H, Flavanone 3-hydroxylase; F3′H, Flavonoid 3′-hydroxylase; F3′5′H, Flavonoid 3′5′-hydroxylase; FNS, Flavonoid synthase; FLS, Flavonol synthetase; UFGT, UDP-glycose flavonoid glycosyltransferase; DFR, Dihydroflavonol reductase; ANS, Anthocyanin synthase; ANR, Afsnthocyanidin reductase; LAR, Leucoanthocyanidin reductase; HCT, Hydroxycinnamoyl acyltransferase; C3H, p-Coumaric acid 3 hydroxylase; CSE, Caffeoyl shikimate esterase; COMT, Caffeic acid O-methyltransferase; F5H, Ferulic acid 5-hydroxylase; CcoAOMT, Caffeoyl-CoA-O-methyltransferase; CCR, Coumarin-CoA reductase; CAD, Cinnamyl alcohol dehydrogenase; PER, Peroxidase; LAC, Laccase. CK: control, no larval infestation; MD: moderate infestation level, 5 larvae per bud; SD: severe infestation level, 10 larvae per bud. The color gradient from red to blue indicates the relative transcript expression levels from high to low.</p>
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<p>Hormone-related gene expression. (<b>a</b>). LOX2, lipoxygenase 2; (<b>b</b>). LOXC, lipoxygenase C; (<b>c</b>). AOC, allene oxide cyclase; (<b>d</b>). OPR3, 12-oxophytodienoate reductase; (<b>e</b>). JAZ1, JAZ protein 1, a key transcriptional repressor during JA signaling; (<b>f</b>). MYC2a, the JA pathway MYC2a transcription factors; (<b>g</b>). MYC2c, the JA pathway MYC2c transcription factors; (<b>h</b>). NPR1, Nonexpressor of pathogenesis-related genes 1 in SA pathway; (<b>i</b>). ICS1, isochorismate synthase 1 in SA pathway. CK: control, no larval infestation; MD: moderate infestation level, 5 larvae per bud; SD: severe infestation level, 10 larvae per bud. The data denoted by the different lower-case letters indicated significant differences between the treatments (DMRT, <span class="html-italic">p</span> &lt; 0.05), where ns represents non-significant and error bars indicate standard deviation.</p>
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<p>The sketch illustrates the response of <span class="html-italic">Camellia sinensis</span> L. to <span class="html-italic">Tambocerus elongatus</span> infestation through secondary metabolism and defense hormone pathways. When infested by <span class="html-italic">Tambocerus elongatus</span>, tea plants activate jasmonic acid, a hormone significantly associated with pest resistance. This activation triggers the induction of flavonoids and lignans, particularly lignin, in the secondary metabolic pathway, thereby enhancing the plant’s resilience against the pest. In this model, solid lines denote pathways that play a pivotal role, and arrows indicate up-regulation.</p>
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25 pages, 2988 KiB  
Article
White Oaks Genetic and Chemical Diversity Affect the Community Structure of Canopy Insects Belonging to Two Trophic Levels
by Elgar Castillo-Mendoza, Leticia Valencia-Cuevas, Patricia Mussali-Galante, Fernando Ramos-Quintana, Alejandro Zamilpa, Miriam Serrano-Muñoz, Juli Pujade-Villar and Efraín Tovar-Sánchez
Diversity 2025, 17(1), 62; https://doi.org/10.3390/d17010062 - 17 Jan 2025
Viewed by 355
Abstract
The hybridization phenomenon increases genetic diversity and modifies recombinant individuals’ secondary metabolite (SMs) content, affecting the canopy-dependent community. Hybridization events occur when Quercus rugosa and Q. glabrescens oaks converge in sympatry. Here, we analyzed the effect of the genetic diversity (He) [...] Read more.
The hybridization phenomenon increases genetic diversity and modifies recombinant individuals’ secondary metabolite (SMs) content, affecting the canopy-dependent community. Hybridization events occur when Quercus rugosa and Q. glabrescens oaks converge in sympatry. Here, we analyzed the effect of the genetic diversity (He) and SMs of Q. rugosa, Q. glabrescens and hybrids on the community of gall-inducing wasps (Cynipidae) and their parasitoids on 100 oak canopy trees in two allopatric and two hybrid zones. Eighteen gall wasp species belonging to six genera and six parasitoid genera contained in four families were identified. The most representative parasitoid genera belonged to the Chalcidoidea family. Abundance, infestation levels and richness of gall wasps and their parasitoids registered the next pattern: Q. rugosa higher than the hybrids, and the hybrids equal to Q. glabrescens. Oak host genetic diversity was the variable with the highest influence on the quantitative SMs expression, richness and abundance of gall wasps and their parasitoids. The influence of SMs on gall wasps and their parasitoids showed the next pattern: scopoletin > quercitrin > rutin = caffeic acid = quercetin glucoside. Our findings indicate that genetic diversity may be a key factor influencing the dynamics of tri-trophic interactions that involve oaks. Full article
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<p>Gall-inducing wasps found in <span class="html-italic">Q. glabrescens</span> × <span class="html-italic">Q. rugosa</span> complex.</p>
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<p>Gall-inducing wasps found in <span class="html-italic">Q. glabrescens</span> × <span class="html-italic">Q. rugosa</span> complex.</p>
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<p>Network related to the positive influence between host oak [genetic diversity (<span class="html-italic">He</span>), secondary metabolites (rutin, caffeic acid, quercetin glucoside, quercitrin, kaempferol glucoside, scopoletin)] and the richness (<span class="html-italic">S</span>) and abundance of canopy gall-inducing wasps and their parasitoids. Nv = normalized value (from 0 to 1), where (1) in the range [0.0–0.22], the influence is very low; (2) in the range [0.22–0.44], the influence is low; (3) in the range [0.44–0.66], there is a medium influence; (4) in the range [0.66–0.88], the influence is high; and (5) in the range [0.88–1], the influence is very high.</p>
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<p>Network related to the negative influence between host oak [genetic diversity (<span class="html-italic">He</span>), secondary metabolites (rutin, caffeic acid, quercetin glucoside, quercitrin, kaempferol glucoside, scopoletin)] and the richness (<span class="html-italic">S</span>) and abundance of canopy gall-inducing wasps and their parasitoids. Nv = normalized value (from 0 to 1), where (1) in the range [0.0–0.22], the influence is very low; (2) in the range [0.22–0.44], the influence is low; (3) in the range [0.44–0.66], there is a medium influence; (4) in the range [0.66–0.88], the influence is high; and (5) in the range [0.88–1], the influence is very high.</p>
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<p>Function that models the behavior of the relationships depicted in the network related to the influences. The <span class="html-italic">X</span> axis shows the normalized values (Nvs) between 0 and 1. The sigmoid function models the behavior of the relationships through qualitative values, which are easier to interpret. We define five zones that represent the influence of the independent variable <span class="html-italic">X</span> on the dependent variable Y, which are (1) in the range [0–0.22], the influence of <span class="html-italic">X</span> on <span class="html-italic">Y</span> is very low; (2) in the range [0.22–0.44], the influence is low; (3) in the range [0.44–0.66], there is a medium influence; (4) in the range [0.66–0.88], the influence is high; and (5) in the range [0.88–1], the influence is very high. See <a href="#app3-diversity-17-00062" class="html-app">Appendix C</a> for more details.</p>
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