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Article

Responses of Dominant Tree Species Phenology to Climate Change in the Ailao Mountains Mid-Subtropical Evergreen Broad-Leaved Forest (2008–2022)

by
Ruihua Ma
1,
Yanling Peng
2,*,
Shiyu Dai
3,4 and
Hede Gong
1,*
1
School of Geography and Tourism, Qilu Normal University, Jinan 250200, China
2
College of Physics and Electronic Engineering, Qilu Normal University, Jinan 250200, China
3
College of Soil and Water Consercation, Southwest Forestry University, Kunming 650224, China
4
Yunnan Key Laboratory of Forest Ecosystem Stability and Global Change, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla 666303, China
*
Authors to whom correspondence should be addressed.
Forests 2026, 17(1), 92; https://doi.org/10.3390/f17010092
Submission received: 16 December 2025 / Revised: 31 December 2025 / Accepted: 7 January 2026 / Published: 9 January 2026
(This article belongs to the Special Issue Abiotic and Biotic Stress Responses in Trees Species—2nd Edition)
Browse Figures
Versions Notes

Abstract

Plant phenology is a sensitive indicator of ecosystem responses to climate change, yet its dynamics and drivers in subtropical montane forests remain poorly understood. Based on the continuous phenological monitoring of 12 dominant tree species from 2008 to 2022 in a mid-subtropical evergreen broad-leaved forest on Ailao Mountains, China, this study analyzed phenological shifts and their climatic drivers. The results show that, (1) unlike the widely reported trends in northern mid-to-high latitudes, spring phenophases (budburst and leaf-out) did not exhibit significant advancing trends, while autumn phenophases (leaf coloration and fall) remained stable; (2) water availability played a dominant role in regulating spring phenology, with both budburst and leaf-out showing significant negative correlations with winter-spring precipitation, and responses varied significantly across hydrological year types; and (3) the life form strongly influenced phenological strategies, with evergreen species exhibiting earlier spring phenology than deciduous species. This study highlights that in seasonally humid subtropical montane forests, water availability exerts a stronger control on phenology than temperature. Our findings underscore the necessity of incorporating precipitation variability and functional trait differences into assessments of forest phenology and ecosystem functioning under future climate change, providing a scientific basis for the conservation and adaptive management of subtropical forests.

1. Introduction

Climate change alters regional humidity and thermal conditions, thereby affecting vegetation microhabitats and soil environments and ultimately leading to changes in vegetation growth dynamics [1]. Plant phenology, which manifests as the timing of recurring plant life-cycle events [2], is a sensitive bio-indicator of ecosystem responses to climate change. Its dynamic variations directly regulate species interactions, community stability, and ecosystem carbon-water-energy exchange processes [3,4,5], while also reflecting variations in regional climatic conditions to some extent [6]. Furthermore, by altering fundamental processes such as the water cycle, soil carbon balance, and plant respiration, shifts in phenology cascade to influence critical aspects of terrestrial ecosystems, with significant implications for biodiversity and habitat conservation [7]. Therefore, elucidating plant phenological changes and their driving mechanisms is crucial for accurately understanding the processes through which ecosystems respond to climate change.
Previous research has demonstrated a widespread trend that in the Northern Hemisphere’s middle and high latitudes under global warming: an advance in spring phenology (leaf-out, flowering), a delay in autumn phenology (leaf coloring, leaf fall), and a consequent extension of the growing season, which has been extensively validated by observations [8,9,10,11]. For instance, in the Mediterranean region since the 1970s, the leaf-out and flowering dates of 29 perennial plant species have advanced by an average of 0.48–0.59 days per year, with the growing season extended by 18 days, a change particularly pronounced at high-altitude areas [12]. Across Europe, the rate of spring phenological advancement during 1971–2000 closely aligned with the magnitude of regional warming, where the temperature sensitivity of leaf-out in deciduous tree species (−7.62 days/°C) was significantly higher than that observed on other continents [9]. These observational facts not only provide robust evidence for phenology serving as a sensitive indicator of climate change but also highlight the crucial role of rising temperatures in driving phenological changes in mid- to high-latitude regions. Attribution analysis further demonstrates that such phenological trends are clearly linked to anthropogenic warming rather than merely natural variability [9,13]. However, attributing phenological changes primarily to temperature faces new conceptual challenges. Recent studies have revealed that plant phenological responses to temperature are not static, with their sensitivity exhibiting heterogeneous patterns of variation over time and across space [14]. In particular, recent years have witnessed new dynamics in phenological responses to climate warming. Since around 2000, the trend of advancing spring phenology in the Northern Hemisphere has markedly slowed or even reversed in some regions. This “attenuation of phenological response” is attributed to multiple mechanisms, including insufficient winter chilling [5,15], asymmetrical day-night warming [16], and physiological threshold limitations in plants [17]. Additionally, although numerous controlled experiments have explored the impact of climate change on plant phenology, most focused on seedlings or saplings [18,19], observations targeting mature trees remain scant. Notably, the phenological responses of saplings and mature trees to the same environmental changes may differ substantially [20], highlighting the limitation of selecting appropriate study subjects in current research and reinforcing the need for further investigations into the phenology of mature trees.
While current research in plant phenology has established a fundamental theoretical framework in which climatic drivers induce phenological dynamics that subsequently lead to ecological effects, significant limitations persist. First, most long-term studies have focused predominantly on temperate, boreal, or Mediterranean climate zones, with inadequate attention devoted to subtropical montane forests—ecosystems characterized by high species diversity and complexly intertwined hydrothermal regimes [12]. These ecosystems are defined by a pronounced dry-wet season alternation (e.g., 85% of annual precipitation in the Ailao Mountains occurs from May to October) and the coexistence of evergreen and deciduous species, which results in phenological response patterns fundamentally distinct from those in high-latitude regions. For example, the long leaf lifespan and conservative nutrient allocation strategy of subtropical evergreen species may result in significantly lower sensitivity to temperature changes than deciduous species [2,21]. However, research on related mechanisms remains scarce, potentially leading to regional representational bias and a lack of functional-type specificity. Second, a predominant focus of prior research has been on the dominant role of temperature, especially in regions where low temperatures constitute the primary limiting factor [22]. Yet, in seasonally dry-wet ecosystems, the regulatory role of water availability may be equally important. A meta-analysis of 63 controlled experiments on ten phenophase responses to precipitation changes found that increased precipitation advanced early-season phenophases and delayed late-season ones, extending reproductive and growing seasons; decreased precipitation delayed leaf-out and advanced leaf coloring, shortening the growing season [23]. This phenomenon primarily arises from the fact that changes in precipitation patterns alter plant water status, modify nutrient acquisition, and adjust survival risks, thereby systematically regulating the initiation and cessation of its life cycle, culminating in variations in the length of the growing season [24]. In high-elevation humid forests (e.g., those in the Ailao Mountains), the interactive effects between temperature and precipitation—for instance, how warm and dry springs inhibit leaf-out—remain a key knowledge gap. Furthermore, climate fluctuations response strategies are likely to differ substantially among key functional tree types (e.g., evergreen vs. deciduous species), yet the mechanism is still unclear.
The mid-elevation humid evergreen broad-leaved forest in the Ailao Mountains National Nature Reserve ranks among China’s best-preserved primary forests in the subtropical region. Boasting diverse tree species composition and complex environmental gradients, it serves as an ideal natural laboratory for exploring climate fluctuations-induced phenological responses. Drawing on long-term continuous phenological observations spanning 2008–2022, this study aims to elucidate the phenological dynamics of the dominant tree species in this ecosystem and the underlying climatic drivers thereof. This study addresses the following research questions: (1) What are the long-term variation trends of key phenological phases in the mid-elevation humid evergreen broad-leaved forest of the Ailao Mountains? (2) Do tree species of different life-forms (e.g., evergreen vs. deciduous species) exhibit divergent phenological responses to climate variability? (3) What are the distinct regulatory roles of temperature and precipitation in driving diverse phenological processes? Specifically, does water availability serve as a key regulatory factor in spring phenology?

2. Materials and Methods

2.1. Study Area

This study was conducted in the Xujiaba region (24°32′ N, 102°01′ E; Figure 1a), a typical mid-elevation humid evergreen broad-leaved forest located in the core area of the Ailao Mountains National Nature Reserve. The reserve is situated in Jingdong County, Pu’er City, Yunnan Province, China, with the study area spanning an elevation range of 2400–2600 m.
Meteorological data from the Xujiaba weather station (located within the study area) indicate a mean annual precipitation of 1931 mm, with ~85% concentrated in the May–October period, and a mean annual air temperature of 11.3 °C—resulting in distinct wet and dry seasons (Figure 1b). The predominant soil type in the study area is loamy alfisols [25]. The reserve lies within a transitional climatic zone between the central and southern subtropics, characterized by pronounced altitudinal zonation. It harbors the largest contiguous area of pristine mid-elevation humid evergreen broad-leaved forest in China. This forest is characterized by a dense and closed canopy, with distinct vertical stratification comprising tree, shrub, and herb layers. The vegetation is abundant in lianas and other woody plants, and boasts a high abundance of epiphytes, predominated by bryophytes and ferns. The dominant tree species include Schima noronhae, Hartia sinensis, Lithocarpus xylocarpus [26,27].

2.2. Data Monitoring

In this study, the 12 selected tree species (8 evergreen and 4 deciduous) within the Ailao Mountains National Nature Reserve are all dominant species in the mid-subtropical evergreen broad-leaved forest of this region. These species represent a substantial proportion of the wet evergreen broad-leaved forest community in Ailao Mountains, and their phenological dynamics can effectively reflect the overall functional characteristics of this ecosystem. Furthermore, to address the research question of “whether trees of different life forms exhibit differential phenological responses to climate variability,” we intentionally included two key functional types: evergreen and deciduous. All selected species were healthy, pest-free mature individuals growing near the meteorological station. Their stable growth condition ensures the reliability of long-term phenological monitoring, while their convenient location facilitates frequent field observations, particularly during critical phenological phases such as budburst and leaf expansion. Each selected individual was tagged with a unique identifier and subjected to regular observations. For each target plant species, 5 to 8 individual were included in the observation cohort. The phenological phases recorded encompassed Bud burst, Leaf expansion, First flowering, Full flowering, Fruiting period, Leaf coloring, and Leaf fall. During periods of rapid phenological change (e.g., Bud burst, Leaf expansion, and First flowering), observations were conducted every other day. For phenological phases such as Fruiting period, Leaf coloring, and Leaf fall, observations were carried out on the 3rd, 11th, 19th, and 26th of each month. In the event of special weather events—including abrupt cold spells, frost, snowfall, or heavy rainfall—the frequency of observations was appropriately increased. Data were recorded on standardized forms during each observation. To minimize systematic error, observations were consistently performed by the same personnel using a combination of visual assessment, binoculars, and other specialized tools. Phenological observation sample trees were selected in the vicinity of the forest meteorological station, facilitating the subsequent analysis of correlations between plant phenology and meteorological factors. Phenological monitoring was consecutively conducted over the period from 2008 to 2022. Detailed phenological information for each target species is summarized in Table 1. Corresponding meteorological data were obtained from the Ailao Mountains Ecological Station.
In this study, the flowering dates were converted to day-of-year (DOY) values for computational and analytical purposes, with 1 January assigned a DOY value of 1, 2 January assigned a value of 2, and so on [28]. The interannual variations in the timing of different phenological phases during the period from 2008 to 2022 are illustrated in Figure 2.

2.3. Classification of Hydrological Years

To quantify the interannual fluctuations in moisture availability and their subsequent impacts on plant phenology in the study area, we classified the hydrological conditions of each observation year based on daily precipitation data collected from the aforementioned meteorological station. The annual precipitation anomaly percentage (Pa) was adopted as the core metric for this objective classification [29].
The Pa was computed as follows: First, the climatological baseline period of this study was defined as 2005–2022. The mean annual precipitation (P_mean) during this period was then calculated to serve as the long-term climatic norm for the study region. Subsequently, for any specified target year, its Pa value was derived using the following formula:
Pa = (P_i − P_mean)/P_mean × 100%
where P_i represents the annual precipitation of the target year. With reference to the drought classification principles outlined in the Chinese meteorological industry standard QX/T 469-2018 [30] and considering the actual precipitation distribution characteristics of the study area, all years were classified into the following five hydrological year types, as shown in Table 2.
This classification scheme offers a standardized, objective framework for defining hydrological year types, thereby laying a robust methodological foundation for subsequent analyses of phenological responses to diverse scenarios of water deficit and surplus.

2.4. Statistical Analysis

All statistical analyses were conducted in RStudio (version 4.4.1) using plant phenological observation data from 2008 to 2022. To assess the significance of variations in plant phenology across years, hydrological year types, and species, multiple comparisons were performed with the LSD test using the agricolae package in R. Furthermore, independent-samples t-tests were employed to examine differences in phenophases among species with distinct life forms. The significance threshold for all statistical tests was set at α = 0.05. To more precisely dissect the influence of meteorological factors on plant phenology, linear mixed-effects models (LMMs) were fitted separately for each phenophase (e.g., leaf expansion, first flowering) using the lmerTest package in R. In these models, the phenophase date was treated as the response variable [31]. Seasonal climate indices were included as fixed effects, while species and life form were incorporated as random effects to account for variation attributable to their inherent biological traits. This modeling framework allowed us to identify the effects of seasonal climatic conditions on phenological progression while accounting for the hierarchical structure and repeated-measures nature of the data. All figures presented in this study were generated using the ggplot2 package in R.
The general model formula is
model <- lmer (DOY ~ Meteorological data1 + Meteorological data2 + (1|Life.form) + (1|Species)

3. Results

3.1. Interannual Variation in Phenophases of the Mid-Montane Wet Evergreen Broad-Leaved Forest in the Ailao Mountains

Based on continuous observational data collected from 2008 to 2022, this study systematically analyzed the interannual variations in phenophases of dominant tree species within the mid-montane wet evergreen broad-leaved forest of the Ailao Mountains. The results revealed that different phenophases exhibited differential responses to climate fluctuations, with more pronounced variations detected in spring and summer phenophases. For spring phenology, the Bud burst (Figure 3a) exhibited distinct interannual fluctuations (R2 = 0.06, p < 0.001) and followed an overall nonlinear trend characterized by an initial advancement and subsequent delay. Additionally, significant interannual differences were detected (p < 0.001). The Leaf expansion (Figure 3b) also exhibited significant interannual variations (R2 = 0.06, p = 0.002) and followed a dynamic pattern largely consistent with that of Bud burst, indicating synchronous responses of spring phenological events to climatic drivers. Regarding reproductive phenology, both First flowering and Full flowering (Figure 3c,d) remained relatively stable across years, with no significant interannual trend detected, implying that flowering may be governed by intrinsic physiological regulation or conserved strategies shaped by long-term adaptation. Similarly, the fruiting period (Figure 3e) remained relatively stable over the entire study period, with the exception of 2010. With regard to autumn phenological events, Leaf coloring (Figure 3f) exhibited fluctuations throughout the observation period, whereas Leaf fall (Figure 3g) remained overall stable, with no significant interannual variation trends detected. Specifically, Leaf coloring displayed certain fluctuations in the early years of the study before stabilizing in later periods, whereas Leaf fall maintained a relatively consistent temporal pattern across all monitoring years.

3.2. Phenological Differences in Mid-Montane Moist Evergreen Broad-Leaved Forests in the Ailao Mountains Among Different Hydrological Years

Based on the annual precipitation anomaly percentage, this study classified the observational years into five hydrological year types and systematically quantified the variation patterns of different phenophases across each hydrological year type. The results further revealed distinct stage-specificity in the phenological responses of plants to hydrological year types. Specifically, spring phenology (Bud burst and Leaf expansion) exhibited significant sensitivity to hydrological year types (Figure 4a,b; p < 0.05). Spring phenological progression in exceptionally dry years was significantly delayed compared to that in wet and exceptionally wet years, while dry and normal years exhibited intermediate transitional response patterns.
Reproductive phenology (First flowering and Full flowering) exhibited weaker responsiveness to hydrological year types (Figure 4c,d; p > 0.05), whereas the Fruiting period exhibited a significant advancement exclusively in wet years (Figure 4e; p < 0.05). Autumn phenology (Leaf coloring and Leaf fall) exhibited no statistically significant response to hydrological year types (Figure 4f,g; p > 0.05).

3.3. Interspecific Differences in Phenophases of the Mid-Montane Moist Evergreen Broad-Leaved Forest in the Ailao Mountains

To gain a more in-depth understanding of the heterogeneity in phenological responses at the species level, we further analyzed the interspecific differences in key phenophases among 12 species. The results revealed significant divergence in phenological timing across species (Figure 5; p < 0.001), reflecting the differential adaptations of their ecological strategies and functional types to climatic factors.
Significant interspecific variation was observed in spring phenophases, specifically Bud burst and Leaf expansion. Bud burst of A. heptalobum, V. duclouxii, and H. sinensis was significantly earlier (mean DOY: 71.5 ± 9.2, 48.7 ± 19.8, 73.3 ± 9.0; p < 0.05). In contrast, S. noronhae and S. perkinsiae exhibited notably later Bud burst (mean DOY: 92.5 ± 20.4 and 98.3 ± 6.0, respectively). Leaf expansion exhibited a comparable interspecific trend.
In terms of reproductive phenology, V. duclouxii and A. heptalobum exhibited the earliest First flowering (mean DOY: 90.8 ± 18.6 and 99.8 ± 10.0, respectively), whereas Full flowering of S. noronhae was concentrated in late summer (mean DOY: 215.5 ± 21.3). However, no significant difference in reproductive phenological traits was detected between deciduous and evergreen species.
The Fruiting period exhibited substantial variation among species. V. duclouxii and A. evodiaefolius initiated fruiting significantly earlier than the other studied species (mean DOY: 213.8 ± 40.0 and 216.5 ± 19.2, respectively), whereas fruiting in S. noronhae and H. sinensis occurred considerably later (mean DOY: 281.2 ± 22.9 and 293.7 ± 45.2, respectively). The large standard deviations (SD) observed for certain species suggest substantial interannual variability in their fruiting phenology.
Autumn phenological events were exclusive to deciduous species, with significant interspecific variation in the onset timing of leaf coloring and leaf fall (p < 0.05). A. heptalobum had the earliest onset of leaf coloring (mean DOY: 267.5 ± 14.87), whereas A. evodiaefolius and S. perkinsiae showed relatively later onsets (mean DOY: 284.8 ± 11.1 and 291.9 ± 7.8).

3.4. Climate Fluctuations as a Driver of Phenological Shifts in the Evergreen Broad-Leaved Forests of the Ailao Mountains

3.4.1. Climate Fluctuations

Based on meteorological observation data spanning from 2008 to 2022, this study quantitatively analyzed the temporal dynamics characteristics and trends of annual mean temperature and annual precipitation in the study area. During the research period, the annual mean temperature showed a statistically significant increasing trend (R2 = 0.26, p = 0.032) (Figure 6a). In contrast, annual precipitation exhibited substantial interannual variability, with a slight decreasing trend that was not statistically significant (Figure 6b).

3.4.2. Correlation Analysis Between Phenology and Climatic Variation

To assess the impact of climate fluctuations on forest phenological trends, we constructed linear mixed-effects models. In this framework, phenological metrics were designated as dependent variables; seasonal temperature and precipitation—spanning spring (March–May), summer (June–August), autumn (September–November), and the preceding winter (December–February)—were incorporated as fixed effects, while species and plant life form were treated as random effects.
Spring phenological events—Bud burst and Leaf expansion—were primarily driven by precipitation. In particular, Bud burst exhibited significant negative correlations with both winter (R = −0.16, p < 0.05) and spring (R = −0.21, p < 0.01) precipitation (Figure 7a). Leaf expansion exhibited highly significant negative correlations with winter precipitation (R = −0.29, p < 0.001), spring precipitation (R = −0.31, p < 0.001), and spring temperature (R = −0.13, p < 0.01) (Figure 7b). These results suggest that elevated winter and spring precipitation significantly promotes both Bud burst and Leaf expansion, whereas the effect of temperature is weaker than that of precipitation. Reproductive phenological events (First flowering and Full flowering) exhibited distinct response patterns. Specifically, both First flowering and Full flowering showed significant negative correlations exclusively with spring temperature (R = −0.11, p < 0.05; Figure 7c,d).
The Fruiting period was strongly driven by thermal conditions, exhibiting a highly significant positive correlation with summer temperatures (R = 0.28, p < 0.001). This finding indicates that warmer summers were associated with delayed fruiting progression, suggesting a lagged response of fruit development to heat accumulation—where elevated temperatures act to slow phenological advancement. No significant linear relationships were detected between autumn phenological events (Leaf coloring and Leaf fall) and the climatic variables examined. This suggests that the progression of autumn phenology in the deciduous forests of Ailao Mountains remained relatively stable throughout the study period, with interannual variations likely regulated by factors other than temperature and precipitation.

4. Discussion

4.1. The Uniqueness of Phenological Responses in Subtropical Montane Forests

Multiple lines of evidence from empirical observations and modeling studies indicate that rising global temperatures are likely to prolong the growing season across many regions worldwide—including numerous tropical areas [32,33,34]. However, this conclusion remains subject to debate, as several studies have reported contradictory findings [35,36]. Drawing on continuous field observations spanning 2008 to 2022, this study systematically characterizes the phenological response patterns of dominant tree species in the mid-montane moist evergreen broad-leaved forest of the Ailao Mountains to climate fluctuations. In contrast to the well-documented pattern of spring phenological advancement and autumn phenological delay observed across mid-to-high latitudes of the Northern Hemisphere [9], spring phenophases (Bud burst and Leaf expansion) in our study area exhibited no significant advancing trend, despite considerable interannual variability. Furthermore, autumn phenophases (Leaf coloration and Leaf fall) showed no discernible long-term directional trend and remained relatively stable throughout the entire observation period. This divergence underscores the unique phenological response mechanisms of subtropical montane forests, which can be attributed to the specific environmental context of our study site: a high-altitude, cool-humid climate, coupled with a distinct seasonal alternation between dry and wet seasons [12]. In typical mid-to-high latitude regions of the Northern Hemisphere—such as the temperate plains and lowlands of North America and Europe—temperature serves as the principal driver of plant phenology [9,37,38,39]. In contrast, in the mid-montane moist evergreen broad-leaved forest of the Ailao Mountains, water availability emerges as the dominant regulatory factor. This finding aligns with observations from Barro Colorado Island, Panama, where increased rainfall has been associated with an extended leaf-growing season [40]. Furthermore, the persistently cloudy, cool, and humid conditions at our study site are likely to buffer temperature extremes [41], thereby contributing to the observed relative stability of phenology amid interannual climatic fluctuations.

4.2. Moisture as a Pivotal Driver of Spring Phenology

As the impacts of climate change on subtropical forests intensify, elucidating the regulatory mechanisms by which key climatic factors—particularly precipitation—mediate tree phenology has become a central focus of contemporary ecological research. While temperature is widely recognized as the primary driver of phenological shifts in temperate and boreal forests [4,5], a contrasting pattern has been documented in a southeastern Malagasy rainforest, where rainfall was found to be significantly correlated with the phenology of 69 tree species [42]. Consistent with this, our findings demonstrate that spring phenology—particularly Leaf expansion—is primarily regulated by winter and spring precipitation rather than temperature. In ecosystems characterized by marked seasonal drought, such as the Ailao Mountains, pre-growing season rainfall likely facilitates Bud burst and Leaf expansion by alleviating soil water deficit [23]. This observed regulatory mechanism is further validated by significant variability in spring phenology across divergent hydrological years. Specifically, spring vegetative phenophases (Bud burst and Leaf expansion) in this forest system display marked sensitivity to hydrological regimes, with phenological dynamics responding distinctly to interannual differences in water availability. This provides compelling evidence that water availability acts as a primary environmental trigger governing the timing of spring phenological events in this region. Moreover, the influence of water availability is consistently positive: elevated precipitation—regardless of whether it occurs in spring or summer—results in the advancement of spring phenology. Augmented winter–spring precipitation mitigates this water deficit while simultaneously boosting soil nitrogen availability. Specifically, higher rainfall levels accelerate the mineralization of organic nitrogen pools and increase the mobility of inorganic nitrogen in the soil solution [43]. This enhanced nitrogen supply in turn supports the biosynthesis of proteins, chlorophyll, and a suite of functional enzymes [44]; these molecules are essential for triggering bud dormancy break, driving cell division, and promoting cell expansion. Collectively, these cascading physiological and biochemical mechanisms may thus jointly underpin the significant advancement of spring phenological stages such as leaf expansion [45]. Therefore, to accurately project how climate change will affect subtropical forest phenology in the future, it is essential to incorporate precipitation pattern shifts into predictive frameworks—moving beyond conventional models that depend exclusively on temperature variables [26,46]. That said, the temporal stability of this precipitation–phenology linkage remains to be verified using long-term, continuous observational series.

4.3. Life-Form Variation Drives Phenological Strategies and Attenuates Their Sensitivity to Climatic Change

Significant differences in spring phenology between evergreen and deciduous species (p < 0.05; Figure 5a,b) are presumably underpinned by distinct trade-offs in leaf functional traits. Furthermore, such species-specific phenological responses are inherently linked to their physiological and life history traits [47,48]. Evergreen species’ efficient nutrient partitioning strategy enables sustained investment in their long-lived photosynthetic leaves while facilitating new vegetative growth. This obviates the need for the considerable nutrient expenditure required to produce a full new leaf canopy each spring, thereby freeing up resources to support earlier flowering [49]. In contrast, deciduous trees—whose leaf flushing is tightly synchronized with specific environmental cues (e.g., cumulative heat requirements)—typically initiate growth later than their evergreen counterparts. This observed phenological pattern stands in clear contrast to the findings reported by Schuster et al. [50]. Such a discrepancy most likely arises from divergent adaptive strategies shaped by local climatic constraints, with the risk of late spring frosts in our study area being a key selective pressure [51]. Although “phenological response attenuation” was not directly detected in this study, the absence of a significant advance in spring phenology across multiple years may potentially be linked to inadequate winter chilling accumulation or intrinsic physiological threshold constraints in plants [15,17].

5. Conclusions and Future Research

Based on 15 years of consecutive field observations, this study systematically examined the response patterns of spring phenology in dominant tree species within the mid-montane moist evergreen broad-leaved forest of the Ailao Mountains to ongoing climate change. Our results demonstrate that water availability acts as the key environmental driver modulating the timing of spring phenological events. Furthermore, variations in life forms have led to distinct phenological strategies among coexisting species. Notably, the lack of a significant advancing trend in spring phenology during the observation period suggests that the sensitivity of subtropical tree species to rising temperatures may be changing under prolonged climate change. Despite identifying these key patterns, this study is subject to certain limitations. Future research should incorporate a broader diversity of understory shrubs, herbaceous plants, and species with divergent functional traits to develop a more comprehensive understanding of phenological responses at the community level. Furthermore, while the present phenological observations follow standardized protocols, a degree of subjective bias remains unavoidable. To advance this field, it is critical to integrate multiple monitoring technologies (e.g., near-surface remote sensing, digital repeat photography, and sensor-based measurements) to enable accurate, non-destructive, and continuous phenological tracking, coupled with physiological analyses. Such an integrated approach would enhance the predictive capacity for structural and functional dynamics of subtropical forests under future climate scenarios.

Author Contributions

Conceptualization, Y.P. and S.D.; methodology, Y.P. and S.D.; software, S.D.; validation, Y.P.; formal analysis, Y.P.; investigation, H.G.; resources, H.G.; data curation, S.D.; writing—original draft preparation, R.M.; writing—review and editing, Y.P.; supervision, Y.P.; project administration, H.G.; funding acquisition, R.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data are available upon request from the corresponding author.

Acknowledgments

The dataset was provided by the National Ecosystem Science Data Center, National Science & Technology Infrastructure of China (http://www.nesdc.org.cn) (accessed on 12 July 2025). Thanks are given to the editors and anonymous reviewers for their valuable comments and suggestions for this study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. (a) Location and elevation map of the study area. (b) Monthly averages of temperature (Ta), precipitation (Prec), and relative humidity (RH) in the study area from 2008 to 2022.
Figure 1. (a) Location and elevation map of the study area. (b) Monthly averages of temperature (Ta), precipitation (Prec), and relative humidity (RH) in the study area from 2008 to 2022.
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Figure 2. Phenological variability of dominant tree species in the study area. (a) Interspecific variation among all studied species. (b) Species-specific phenological variation, with colored vertical dashed lines denoting the mean date of each phenophase. Note: Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae).
Figure 2. Phenological variability of dominant tree species in the study area. (a) Interspecific variation among all studied species. (b) Species-specific phenological variation, with colored vertical dashed lines denoting the mean date of each phenophase. Note: Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae).
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Figure 3. Interannual variation in key phenological phases of dominant tree species in the study area. Note: Lowercase letters denote statistically significant differences among years (p < 0.05). The red horizontal dashed line represents the mean value for each phase over the study period (2008–2022), and the curve illustrates the interannual trend. Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae). The color of the bars is solely used to distinguish between different years and has no statistical significance.
Figure 3. Interannual variation in key phenological phases of dominant tree species in the study area. Note: Lowercase letters denote statistically significant differences among years (p < 0.05). The red horizontal dashed line represents the mean value for each phase over the study period (2008–2022), and the curve illustrates the interannual trend. Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae). The color of the bars is solely used to distinguish between different years and has no statistical significance.
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Figure 4. Variations in phenophases among different hydrological year types. Note: Different lowercase letters denote significant differences (p < 0.05) in phenology among years. Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae).
Figure 4. Variations in phenophases among different hydrological year types. Note: Different lowercase letters denote significant differences (p < 0.05) in phenology among years. Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae).
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Figure 5. Interspecific variation in phenological phases of the dominant tree species. Note: Different lowercase letters denote statistically significant differences among species (p < 0.05), and the red horizontal dashed line represents the mean value of each species for each phenological phase. Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae). * statistically significant difference at p < 0.05, ** at p < 0.01, *** at p < 0.001.
Figure 5. Interspecific variation in phenological phases of the dominant tree species. Note: Different lowercase letters denote statistically significant differences among species (p < 0.05), and the red horizontal dashed line represents the mean value of each species for each phenological phase. Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae). * statistically significant difference at p < 0.05, ** at p < 0.01, *** at p < 0.001.
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Figure 6. Key meteorological parameters (annual mean temperature and annual precipitation) in the study area, 2005–2022.
Figure 6. Key meteorological parameters (annual mean temperature and annual precipitation) in the study area, 2005–2022.
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Figure 7. Impact of climatic factors on different phenological phases. Note: Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae). * statistically significant difference at p < 0.05, ** at p < 0.01, *** at p < 0.001.
Figure 7. Impact of climatic factors on different phenological phases. Note: Leaf coloring and Leaf fall are based solely on deciduous tree species (A. heptalobum, A. evodiaefolius, and S. perkinsiae). * statistically significant difference at p < 0.05, ** at p < 0.01, *** at p < 0.001.
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Table 1. Plant species information.
Table 1. Plant species information.
No.Species (Full Name)Species (Conservative)Family/GenusLife Form
1Lithocarpus xylocarpusL. xylocarpusFagaceae/LithocarpusEvergreen
2Lithocarpus hanceiL. hanceiFagaceae/LithocarpusEvergreen
3Castanopsis rufescensC. rufescensFagaceae/CastanopsisEvergreen
4Manglietia insignisM. insignisMagnoliaceae/ManglietiaEvergreen
5Schima noronhaeS. noronhaeTheaceae/SchimaEvergreen
6Hartia sinensisH. sinensisTheaceae/HartiaEvergreen
7Vaccinium duclouxiiV. duclouxiiEricaceae/VacciniumEvergreen
8Camellia forrestiiC. forrestiiTheaceae/CamelliaEvergreen
9Illicium macranthumI. macranthumSchisandraceae/IlliciumEvergreen
10Acer heptalobumA. heptalobumSapindaceae/AcerDeciduous
11Acanthopanax evodiaefoliusA. evodiaefoliusAraliaceae/AcanthopanaxDeciduous
12Styrax perkinsiaeS. perkinsiaeStyracaceae/StyraxDeciduous
Table 2. Classification of hydrological year types based on Pa.
Table 2. Classification of hydrological year types based on Pa.
Exceptionally Dry YearPa ≤ −50%
Dry Year−50% < Pa ≤ −20%
Normal Year−20% < Pa < 20%
Wet Year20% ≤ Pa < 50%
Exceptionally Wet YearPa ≥ 50%
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Ma, R.; Peng, Y.; Dai, S.; Gong, H. Responses of Dominant Tree Species Phenology to Climate Change in the Ailao Mountains Mid-Subtropical Evergreen Broad-Leaved Forest (2008–2022). Forests 2026, 17, 92. https://doi.org/10.3390/f17010092

AMA Style

Ma R, Peng Y, Dai S, Gong H. Responses of Dominant Tree Species Phenology to Climate Change in the Ailao Mountains Mid-Subtropical Evergreen Broad-Leaved Forest (2008–2022). Forests. 2026; 17(1):92. https://doi.org/10.3390/f17010092

Chicago/Turabian Style

Ma, Ruihua, Yanling Peng, Shiyu Dai, and Hede Gong. 2026. "Responses of Dominant Tree Species Phenology to Climate Change in the Ailao Mountains Mid-Subtropical Evergreen Broad-Leaved Forest (2008–2022)" Forests 17, no. 1: 92. https://doi.org/10.3390/f17010092

APA Style

Ma, R., Peng, Y., Dai, S., & Gong, H. (2026). Responses of Dominant Tree Species Phenology to Climate Change in the Ailao Mountains Mid-Subtropical Evergreen Broad-Leaved Forest (2008–2022). Forests, 17(1), 92. https://doi.org/10.3390/f17010092

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