Responses of Trees and Forests to Climate Change

This study aims to analyze the driving factors and threshold responses of the NDVI across different regional scales in Hunan Province, revealing the main influences on vegetation cover and the corresponding threshold effects and providing essential data for precise future afforestation planning. We use NDVI data and its associated driving factors, employing correlation analysis methods to investigate the spatial differentiation and threshold effects of vegetation driving factors at different regional scales. First, various analytical techniques, including Sen’s trend analysis, the Mann–Kendall significance test, and the Hurst index, are applied to assess changes in vegetation cover between 2000 and 2020 and to predict future trends. Second, to explore the differences in vegetation’s driving mechanisms at different regional scales, the optimal parameters-based geographic detector model is employed, which integrates continuous variable discretization methods and selects the optimal parameter set by maximizing explanatory power. This approach is particularly suitable for analyzing nonlinear relationships. Lastly, threshold regression analysis is conducted on the key driving factors identified through the optimal parameters-based geographic detector model. The results show that vegetation cover in most areas of Hunan significantly increased from 2000 to 2020; however, our predictions suggest slight degradation in the future. The optimal parameters-based geographic detector model identified topography and geomorphology as the primary factors affecting the spatial and temporal distribution of the NDVI, with notable regional differences in other factors. The influence of natural factors has weakened over time, while anthropogenic activities increasingly affect vegetation. Moreover, dual-factor influences exhibit stronger explanatory power than single-factor influences. The threshold response analysis reveals that slope is a key factor influencing the NDVI, with a positive threshold relationship observed at both the provincial and subregional scales, although the threshold points vary by subregion. The temperature and NDVI are negatively correlated, with varying threshold points across regions. The abovementioned research findings suggest that future afforestation efforts in Hunan should take into account the distinct characteristics of each subregion. Afforestation strategies should be tailored based on the specific threshold relationships observed in each area to enhance their effectiveness. Full article

Aulonemia queko Goudot (Poaceae, Bambusoideae) is a species of great cultural importance that has been used as a non-timber forest product in Andean forests for centuries. Despite inhabiting montane forests vulnerable to deforestation, its distribution has not been thoroughly assessed for conservation. This study analyzes its potential distribution at the regional scale (the four countries where it is distributed) and locally (in greater detail within Ecuador), using presence records and climatic and land-use data. Maxent was identified as the best algorithm, achieving high values of AUC, TSS, sensitivity, and specificity. At a regional level, A. queko is estimated to occupy approximately 264,540 km², mostly in Peru, with small areas in Bolivia. In Ecuador, the historical scenario showed the widest distribution, while the current–near-future scenario (20–40–SSP126) presented a more stable model. Temperature and rainfall represented critical factors in defining suitable habitats, as A. queko is highly sensitive to seasonal moisture availability. Land-use changes have reduced potential habitats by more than 35%, underscoring an intensified threat of habitat loss in these biodiversity-rich regions. However, projected climate changes pose an even greater impact, significantly reducing potential distribution. Our findings highlight the compelling effects of both climate-change-driven and human-driven land-use change on the future persistence of A. queko and emphasize the urgent need for targeted conservation strategies to protect its core habitats. Full article

Camphora longepaniculata is an endangered evergreen tree listed as National Class II Protected Tree Species in China, highly valued for its medicinal and economic importance. Currently, research on this species has primarily focused on its pharmaceutical properties, while its potential distribution and responses to climate change remain insufficiently explored. In this study, 36 valid occurrence records and 11 environmental variables were utilized to predict its potential distribution and assess its response to future climate scenarios. The MaxEnt model revealed that the current distribution of C. longepaniculata largely aligns with its predicted suitable habitats, with the primary range located in Sichuan Province. Furthermore, this model identified the highly suitable habitats to be predominantly concentrated in Sichuan and Shaanxi Provinces under climate change. Among the environmental variables, annual precipitation (bio12), minimum temperature of the coldest month (bio6), and elevation (dem) were the most influential, collectively contributing over 70% to the model’s predictive accuracy. Future climate projections compared to the current distribution suggest a northward expansion of suitable habitats for C. longepaniculata, although Sichuan Province is predicted to remain the core habitat under future scenarios. Kernel density analysis of occurrence points indicated that the largest concentration of distribution points is near the Sichuan Basin, reinforcing the importance of this region as a stronghold for the species. Based on the results of potential distribution and kernel density analysis, in situ conservation, artificial cultivation, and the establishment of wild protected areas and local germplasm banks are recommended for stable, suitable habitats, such as Sichuan Province and parts of Yunnan and Guizhou Provinces. This study not only sheds light on the potential geographical distribution of C. longepaniculata and its response to climate change but also provides a scientific basis for the development of targeted conservation strategies for this species. Full article

(1) Background: Global warming has intensified dry heatwaves, threatening urban tree health and ecosystem services. Crown damage in trees is a key indicator of heat stress, linked to physiological changes and urban habitat characteristics, but the specific mechanisms remain to be explored. (2) Methods: This study investigated the heatwave-induced crown damage of Wuhan’s urban tree species, focusing on the influence of physiological responses and urban habitats. Crown damage was visually scored, and physiological responses were measured via stomatal conductance (Gs) and transpiration rate (Tr). (3) Results: Significant interspecific differences in crown damage were identified, with Prunus × yedoensis showing the highest degree of crown damage, while Pittosporum tobira displayed the lowest. A strong correlation was observed between crown damage and Gs and Tr, albeit with species-specific variations. The Degree of Building Enclosure (DegBE) emerged as the most prominent habitat factor, with a mitigating effect on crown damage, followed by the Percentage of Canopy Coverage (PerCC), in contrast with the Percentage of Impermeable Surface (PerIS) that showed a significant positive correlation. (4) Conclusions: The above findings suggest that species traits and habitat configurations interact in complex ways to shape tree resilience under heatwave stress, informing strategies for urban vegetation protection against heat stress in Central Chinese cities. Full article

Damage caused by snowfall can result in broken crowns and trunks and even lead to the uprooting of forest trees. Damage or death of forest trees creates forest gaps and alters overall forest demographics, but predicting the exact nature and influence of this damage remains challenging. In general, the effects of various biotic and abiotic factors on snow damage remain understudied. To address this gap in knowledge, we conducted a meta-analysis of existing literature, ultimately screening 38 manuscripts that describe 142 plant species. Our findings indicate that snow damage significantly reduced annual litterfall, Leaf Area Index, canopy density, abundance, and area at breast height when considering plant communities. However, snow damage also tended to significantly increase Shannon’s Diversity Index, Simpson’s Diversity Index, Pielou’s Evenness Index, and diameter at breast height. In addition, at the population level, snow damage was found to significantly reduce density, abundance, and annual litterfall while significantly increasing diameter at breast height. Further, the response of different forest vegetation community characteristics to snow damage is significantly influenced by factors such as forest type, elevation, slope, and aspect. Full article

Climate change models predict temperature increases, which may affect germination, an important stage in the recruitment of individuals in agroecosystems. Therefore, it is crucial to conduct research on how temperature will impact the germination of multipurpose native species. Leucaena diversifolia (Schltdl.) Benth. is native to America and is commonly cultivated around the world due to having a high protein content in seeds, and their trees are used in agrosilvopastoral systems because they fix nitrogen and provide shade and cattle feed. However, climate change affects the critical phases of its life cycle and influences its growth, reproduction, phenology, and distribution. To assess the germination performance of Leucaena diversifolia under different temperatures throughout thermal times, we estimated germination variables and determined cardinal temperatures and thermal time; we also analysed germination and potential distribution under two climate change scenarios. We found significant variations in seed germination (78–98%) and differences in cardinal temperatures (Tb = 5.17 and 7.6 °C, To = 29.42 and 29.54 °C, and Tc = 39.45 and 39.76 °C). On the other hand, the sub-optimal and supra-optimal temperature values showed little differences: 51.34 and 55.57 °Cd. The models used showed variations in germination time for the analysed scenarios and the potential distribution. We confirm that the populations and distribution of L. diversifolia will be altered due to climate changes, but the species retains the ability to germinate under warmer conditions. Full article