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Article

Quantifying Climate Change Impacts on Romanian Forests: Indicators of Resilience and Vulnerability

by
Serban Chivulescu
1,
Diana Pitar
1,
Alexandru Claudiu Dobre
1,2,*,
Luminița Mărmureanu
1,3,
Ștefan Leca
1 and
Ovidiu Badea
1,2
1
Department of Forest Monitoring, “Marin Drăcea” Romanian National Institute for Research and Development in Forestry, 128 Eroilor Blvd., 077190 Voluntari, Ilfov, Romania
2
Forest Management Planning and Terrestrial Measurements, Department of Forest Engineering, Faculty of Silviculture and Forest Engineering, “Transilvania” University, 1 Ludwig van Beethoven Str., 500123 Brașov, Brașov, Romania
3
National Institute for Earth Physics, 12 Călugăreni Str., 077125 Măgurele, Ilfov, Romania
*
Author to whom correspondence should be addressed.
Forests 2025, 16(6), 941; https://doi.org/10.3390/f16060941
Submission received: 27 April 2025 / Revised: 27 May 2025 / Accepted: 31 May 2025 / Published: 3 June 2025
(This article belongs to the Special Issue Ecosystem-Disturbance Interactions in Forests)
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Abstract

As climate change intensifies globally, understanding forest ecosystem responses becomes crucial for maintaining biodiversity and ecosystem services. Quantitative insights into forest resilience and vulnerability in Romania were obtained by integrating climate indicators with forest stand responses across 400 km2 of experimental forests spanning 13 forest districts from 2013–2022. Climate analysis examined R10mm trends (heavy rainfall days) and warm spell duration index (WSDI) patterns from 1950–2022, while forest assessment used correlation matrix analysis and principal component analysis to evaluate relationships between environmental and structural variables. R10mm trends varied from −1.4 to 1.8 days per decade, showing significant changes in eastern Romania and Western Carpathians. WSDI revealed increasing warm spells, particularly in western regions (2 days per decade). Strong correlations between elevation and precipitation (r = 0.615) emerged, with PCA showing these as primary resilience drivers, explaining 56.7% of variance. Species analysis found that fir, beech, and spruce show strong climate resilience with healthy regeneration across conditions, while sessile oak and hornbeam face greater challenges from changing aridity patterns. The work combines long-term management data with climate trends, providing the first comprehensive assessment of climate–forest interactions in Romanian ecosystems. Integration of climate indices with forest parameters reveals elevation-precipitation gradients as key resilience indicators, offering practical guidance for forest managers to protect resilient species while supporting vulnerable ones facing environmental pressures.

1. Introduction

Forest ecosystems globally face increasing pressures from changing environmental conditions [1,2,3,4,5], impacting their stability and the essential services they provide [6,7,8]. Forest ecosystems provide numerous essential services [4,5], including biodiversity conservation, water cycle regulation, erosion control, habitat provision, carbon sequestration, and provisioning of wood and non-wood products [8]. However, climate change, characterized by increased water scarcity and drought frequency, alters these ecosystems’ structure and function [9]. Drought can lead to reduced forest productivity, canopy defoliation, tree mortality, and altered regeneration patterns [10], impacting the carbon cycle at both the stand and landscape levels [11,12].
European forest policies have shifted towards sustainable and climate-resilient forest management to ensure ecosystem functioning and the continued provision of ecosystem services, including carbon sequestration [13,14]. Forest carbon accumulation is influenced by various factors, including precipitation, temperature, light availability, atmospheric CO2 concentration, and nitrogen deposition [15,16].
To address these challenges, scientists and forest managers are working to develop innovative solutions [17]. These include selective breeding of drought-tolerant tree species, improved forest management practices, and the use of advanced technologies to monitor forest health and predict the impacts of climate change. By taking a proactive approach, we can help ensure the long-term health and resilience of our forests.
Romania’s forests, known for their rich biodiversity and ecological significance, face unprecedented challenges due to climate change. The gradual rise in global temperatures, combined with shifting precipitation patterns and more frequent extreme weather events, is reshaping the dynamics of forest ecosystems [18,19,20]. With its diverse forest landscapes from lowland plains to mountainous regions, Romania is experiencing these pressures firsthand [21]. Species such as beech (Fagus sylvatica), spruce (Picea abies), oak (Quercus spp.), and fir (Abies alba), which are vital to the ecological balance and economic health of the country [22], are particularly vulnerable to these changes [23,24].
The impact of climate change on forest ecosystems is complex [25,26,27] and multifaceted, involving shifts in species composition, altered growth patterns, and increasing susceptibility to pests and diseases [28,29,30]. In Romania, these changes are already evident in the form of increased tree mortality, disrupted regeneration processes, and fluctuations in forest stand structure [31]. The interaction of climate factors, such as temperature, precipitation, and aridity, with forest health is not yet fully understood, making it critical to investigate these relationships in depth [32,33,34,35,36].
This study seeks to explore how Romania’s forests are responding to the evolving climate, focusing on a 400 km2 (40,000 hectare) area of experimental state-owned forests across 13 forest districts. Romanian forests currently cover approximately 6.9 million hectares (~29% of total land area) [37], being characterized by high biodiversity, and the changes due to population growth and land use have historically affected forest dynamics.
By analyzing key environmental variables—such as precipitation, aridity, and elevation—and their influence on forest dynamics, this research also aimed to shed light on the resilience of different species and forest types. Particular attention was given (1) to understand how fir, beech, and spruce, among others, respond to climate stressors such as drought and heatwaves and (2) to examine the correlations between climatic conditions and forest health indicators, like stand structure, regeneration capacity, and species composition.
Despite the fact that it was meant to study forests under diverse ecological and management conditions, specific human pressures (e.g., pollution, fragmentation, intensive tourism, illegal logging) were not directly measured in each area. While management practices provide some insight into human influence, the absence of detailed data on these pressures prevents us from directly connecting them to the resilience and vulnerability of the forests we observed. In order to better understand and quantify these impacts, climate indicators—including the warm spell duration index (WSDI), extreme precipitation (R10mm) and aridity index—were included in the study alongside ecological and forest management data. The analysis utilized R10mm and WSDI climate data up to the year 2022 to align precisely with the available forest management records (2013–2022), ensuring consistent temporal correspondence between climatic conditions and forest ecological parameters.
Ultimately, the final outcome of this research is to provide quantitative insights into forest resilience and vulnerability by integrating climate change indicators and forest stand responses. These findings will support the development of adaptive forest management strategies. As climate change continues to intensify, forest managers in Romania will need to integrate new approaches that enhance the resilience of forests to environmental stress. The findings from this study will contribute to the development of long-term strategies aimed at safeguarding the health and productivity of Romanian forests, ensuring that they continue to provide essential ecosystem services for future generations.

2. Materials and Methods

2.1. Location and Description of the Study Area

The study was conducted in Romania, a country situated in Eastern Europe, known for its diverse and extensive forest landscapes. The research focused on 400 km2 (40,000 hectare) of experimental state-owned forests spread across 13 forest districts (Table 1), administrated by the National Institute for Research and Development in Forestry “Marin Drăcea”. This research included management information covering a ten-year period from 2013 to 2022. This area was chosen to represent a variety of ecological conditions and management practices, making it a suitable and representative sample for assessing the impact of climate change on Romanian forest ecosystems. Although two of the forest areas surveyed are relatively small (19 ha and 48 ha), they were deliberately chosen to represent distinct ecological zones and management approaches, ensuring a comprehensive assessment of forest dynamics.
The study area is geographically diverse, encompassing a wide range of elevations from as low as 51 meters above sea level in the plains to 1037 meters in the mountainous regions (Figure 1, Table 1). This altitudinal gradient covers three main types of relief: plains, hills, and mountains, offering a representative cross-section of Romania’s forested landscapes. The varied terrain plays a crucial role in the microclimatic conditions, influencing species distribution, forest structure, and ecological processes.
The species composition within the study area reflects the ecological diversity of Romania’s forests. Dominant species include beech (Fagus sylvatica), which thrives in both lowland and montane regions, spruce (Picea abies), more commonly found at higher elevations, as well as various species of oak (Quercus spp.) and fir (Abies alba). These species are integral to the forest ecosystems, contributing to both biodiversity and ecosystem services such as carbon sequestration, water regulation, and soil stabilization.
Forest stand structures within the study area are classified into two primary categories: even-aged and uneven-aged stands. Even-aged stands are typically managed for timber production, while uneven-aged stands, which display a more natural age-class distribution, are often managed for biodiversity conservation and ecological resilience. The management of these forests varies, reflecting different approaches to sustainable forestry, including silvicultural treatments designed to enhance resilience to climate change.
The region experiences a temperate climate, with distinct seasonal variations in temperature and precipitation. The average annual precipitation ranges between 400 and 800 mm, depending on elevation and geographic location [38]. Temperature and precipitation patterns in the study area have shown increasing variability in recent decades, with noticeable shifts in extreme weather events, including droughts and heatwaves [39]. These changes in climate variables have had significant implications for forest growth, health, and regeneration processes, which are central to the focus of this research [32,33,34].

2.2. Descriptive Statistics and Correlation Analysis

The statistical analysis for this research involved both descriptive statistics and correlation matrix assessments. These analyses were conducted in R environment, using the R PASTECS package [40], designed for managing and analyzing complex ecological datasets. This package is particularly well-suited for forestry research, where the need to explore large datasets with multiple variables is critical. Calculating the following statistical parameters—minimum, maximum, mean, standard deviation, variance, and coefficient of variation—underlined the distribution and variability of forest ecosystem attributes across the study area.
The variables analyzed included slope, elevation [41], soil litter, stand structure, stand volume, precipitation, and the aridity index (Table 2). These parameters were chosen due to their importance in understanding forest health and climate resilience, being derived from forest management plans. The descriptive statistics allows evaluation of the forest stand characteristics within the study area. These statistical measures capture the variability in forest conditions and identify potential trends in ecosystem response to climate changes [42].
In addition to descriptive statistics, a correlation matrix, based on the Pearson coefficient, was used to investigate the relationships between climatic variables (e.g., precipitation, aridity index) and forest characteristics (e.g., stand volume, species composition). The correlation matrix provided a structured approach to identify significant linkages between variables, aiding in the understanding of how climate factors impact forest structure and dynamics.
To further explore and reduce the dimensionality of the dataset, a principal component analysis (PCA) was performed. PCA is a multivariate technique that simplifies the complexity of high-dimensional data while retaining its essential patterns [43,44].
To better understand the complex interactions between environmental factors and forest resilience, principal component analysis (PCA) was used to reduce dimensionality and identify the most influential structural and climatic variables. By transforming the original dataset into a smaller set of uncorrelated components, PCA facilitated a more comprehensive interpretation of forest ecosystem dynamics, allowing the identification of the main factors affecting forest health and productivity. PCA was applied to a diverse set of variables relevant to forest structure and resilience to climate change, including species composition, stand volume, regeneration area, elevation, and aridity index. This approach helped to reveal distinct patterns in how these variables interact, highlighting key environmental gradients that shape forest responses to climate change. By capturing the most influential factors in a small number of components, PCA provided a structured framework for assessing forest vulnerability, particularly in terms of drought sensitivity and species-specific resilience. To ensure the reliability of PCA-derived insights, the analysis was complemented by correlation assessments, validating significant relationships between climatic stressors and forest responses. This integrative approach strengthened the interpretation of forest resilience indicators and allowed a more accurate assessment of adaptive management strategies. By identifying the dominant environmental and structural factors influencing forest stability, the PCA supported a more evidence-based approach to forest conservation and climate change adaptation planning.
Several R packages were used within the R Studio environment for this analysis:
  • corrr [45]: This package was employed to calculate and explore the correlations among variables, helping to identify significant relationships between climatic factors and forest conditions.
  • ggcorrplot [46]: This package provided an effective way to visualize the correlation matrices, making the relationships between variables easier to interpret through aesthetically clear correlation plots.
  • FactoMineR (v25i01.R) [47]: The core PCA was conducted using this package, which enabled dimension reduction and helped uncover the latent structure of the data. This was particularly useful for identifying the key variables driving the observed patterns in forest ecosystems.
  • factoextra [48]: This package was used to extract and visualize the PCA results, offering a more accessible and comprehensive interpretation of the multivariate relationships.
Overall, the combined use of descriptive statistics, correlation matrices, and PCA allowed for a detailed analysis of the relationships between climate variables and forest conditions, enabling the identification of key trends and vulnerabilities in Romanian forest ecosystems.

2.3. Analytical Frameworks and Contextual Insights

The study relies on a combination of field-based data, and climate datasets (E-OBS 29.0e) [49] to expansively analyze the dynamics of forest ecosystems in relation to climate variability and environmental conditions.
Forest Management Plans: These plans serve as a primary data source, providing detailed information about forest characteristics, including area, average age, species composition, volume, growth rates, and regeneration status. These records, collected over time, allow for a thorough assessment of changes in forest stand structure and productivity, which is critical for understanding long-term ecological trends.
Climate Data: The study utilizes the E-OBS datasets [49], which offer data with sufficient resolution essential for understanding regional climate patterns. Other climate datasets, such as national records, have not been used due to restricted access and lack of availability of open sources. Based on these datasets the following parameters were computed:
  • Warm Spell Duration Index (WSDI): Derived from E-OBS data at a 0.1° spatial resolution, WSDI quantifies the number of days within a year where warm spells (above the 90th percentile of daily maximum temperature) occur. This index provides information about changes in temperature extremes that can impact forest health and resilience.
  • R10mm Index: This index measures the number of days per year when daily precipitation exceeds 10 mm, and is derived from climate data at a 0.1° spatial resolution.
We used this parameter to characterize changes in heavy rainfall events, which are important for assessing the availability of water resources for forest growth and the potential for stress due to excessive precipitation or drought.
For both indices (R10mm and WSDI), trends were analyzed for the 1950–2022 period using the Mann–Kendall test [50,51] to assess statistical significance (p < 0.05) and Sen’s Slope to quantify the rate of change [52]. Using the Mann–Kendall test, we highlight that the observed trend is unlikely to be due to random variability. The rate of change was quantified using Sen’s Slope estimator, providing an indication of the magnitude of the trend, expressed as days per decade for both WSDI and R10mm.
Aridity Index: Calculated at a 30 min spatial resolution, the aridity index indicates the moisture availability in the region. This parameter is extracted from the global aridity index data set (1970–2100) and is computed as the ratio between annual precipitation versus annual potential evaporation [53]. This metric is particularly relevant for understanding how changes in climate conditions, such as increased temperatures or altered precipitation patterns, may influence the water balance and thus the health of forest stands.
The focus of the research was mainly on temperature, precipitation, and aridity indices. Projected changes in CO2 concentrations and air pollutants, although important, were outside this study’s scope but could be addressed in future research.

3. Results

3.1. Precipitations and Temperature Trends in Romania

To properly evaluate precipitation in the studied area, we calculated the R10mm trends for all of Romania, highlighting the regions where precipitation patterns have changed over the years (Figure 2); the R10mm trend, varied across the study area, ranging from −1.4 to 1.8 days per decade. However, statistical significance was observed only in parts of eastern Romania and the Western Carpathians. This variation highlights the regional differences in precipitation patterns and their potential implications for forest health and resilience, particularly in the context of changing climatic conditions. Areas experiencing a significant increase in R10mm days may face enhanced flooding risks, while those with a decreasing trend could be at greater risk of drought.
Additionally, the mean annual number of warm days recorded between 1950 and 2022, expressed by the WSDI, ranged from 1 to 4 days, with higher values (greater than 3 days) observed in north and southwestern Romania (Figure 3).
The trend of increasing warm-wave days is statistically significant across most of the country, particularly in the western half, where the average increase is approximately 2 days per decade. The presence of a significant trend implies that the increase in warm-spell days is systematic and meaningful, rather than a product of short-term fluctuations. This has important ecological implications, as prolonged heatwaves can increase drought stress, tree mortality, and alter forest species composition, requiring adaptive forest management strategies.
This upward trend in WSDI underlines that heat stress on forest ecosystems can affect species composition, regeneration patterns, and overall ecosystem health, especially in specific forest districts (i.e., 4016, 4004, 1609) where the identified positive trends suggest an increased heat stress up to 4 days per decade (Figure 3).

3.2. Characterization of Analyzed Management Units

The following statistical analysis of the forest ecosystem variables provides an overview of the diverse environmental and ecological conditions present across Romania. A total of 21,367 management units (components of the 13 forest districts) were analyzed for various variables as detailed in Table 2.
Elevation measurements varied from 51 m to 1037 m above sea level, with an average elevation of 556 m. The high standard deviation of 261.37 and variance of 68,317.34 reflect the significant altitudinal gradient present throughout the country, transitioning from lowland plains to mountainous areas. This variability in elevation plays a crucial role in influencing microclimates and species composition across different management units.
The soil litter variable is a scale from 1 to 4, where 1 represents no litter and 4 indicates a continuous and thick litter layer. In all of the sites analyzed, values ranged from 1 to 4, with an average of 3, suggesting a generally well-developed litter layer. A standard deviation of 0.74 and a variance of 0.55 indicated moderate uniformity in soil litter conditions across the sampled management units, although specific areas exhibited higher or lower soil litter quality.
In terms of stand structure, which reflects whether the forests are even-aged or uneven-aged, the values ranged from 1 to 4, with 1 representing even-aged stands, 2 indicating relatively even-aged stands, 3 for relatively uneven-aged stands, and 4 for uneven-aged stands. The average value was 2, suggesting a predominance of relatively even-aged stands. A standard deviation of 0.81 and a coefficient of variation of 37% suggest a mix of stand structures across the management units, indicating a balanced distribution between managed forests and more natural, uneven-aged stands throughout the diverse relief and climatic conditions of Romania.
Regarding stand volume, the analysis revealed a wide range from 0 to 711 m3 ha−1, with an average of 85 m3 ha−1. The high standard deviation (97.23) and variance (9454.16) indicate substantial differences in stand volume across the management units, likely reflecting variations in forest age, species composition, and management practices across the various ecological conditions in Romania.
The mean annual precipitation across the management units varied from 399.97 mm to 802.73 mm, with an average of 605.99 mm. The relatively low coefficient of variation (15%) and standard deviation (89.13) suggest that while some variability exists, precipitation levels remain fairly stable across the country.
The aridity index, which measures the balance between precipitation and evapotranspiration, varied from 0.44 to 1.08, with an average of 0.87. The low standard deviation (0.17) and variance (0.03) indicate relatively consistent aridity conditions across the management units, although regions with higher elevation and greater precipitation tend to experience lower levels of aridity. This index is particularly relevant for understanding drought stress in forests, which is a key factor for resilience to climate change.
The species composition in the study area, expressed by the number of species present per management unit, ranged from 1 to 16 species, with an average of 6 species per unit. The standard deviation of 4.29 and variance of 18.46 suggest substantial biodiversity within the forest stands, which are distributed across the diverse ecological conditions found throughout Romania.
Finally, the regeneration area showed considerable variability, ranging from 0 to 9 ha per management unit, with an average of 0.70 ha. The high coefficient of variation (232%) and standard deviation of 1.63 suggest that while some management units demonstrate significant regeneration activity, others show limited natural regeneration.

3.3. The Interaction Between Environmental and Ecological Parameters

The correlation matrix highlighted key relationships among environmental and ecological variables in Romania’s forests (Figure 4). A weak positive correlation (0.289) between slope and elevation indicated that steeper terrains are often at higher elevations, affecting microclimates and species distribution. Notably, elevation and mean precipitation were strongly correlated (0.615), suggesting that higher elevations receive more rainfall, which is crucial for biodiversity.
Increased precipitation correlated positively with soil litter (0.304) and stand structure (0.277), reinforcing the idea that moisture enhances soil fertility and supports complex ecosystems. The correlation between stand structure and regeneration area (0.368) suggested that diverse forests foster natural regeneration, which is vital for ecosystem health.
Conversely, weak negative correlations between species diversity and slope (−0.162) and elevation (−0.126) indicated that environmental stressors in steep and elevated terrains may limit species richness. Regeneration areas showed weak positive correlations with soil litter (0.173) and mean precipitation (0.120), but a negative weak correlation with species composition (−0.129), implying that favorable conditions for regeneration may not always enhance biodiversity. These findings underscore the importance of understanding ecological interdependencies to develop effective forest management strategies that bolster resilience and biodiversity amid climate change.
The PCA on the normalized dataset highlighted key environmental and ecological relationships within Romania’s forests (Figure 5). The first three principal components captured 56.7% of the total variance, with the first component (Dim.1) alone accounting for 30.1%. Dim.1 was predominantly influenced by elevation and mean precipitation, suggesting that these factors are crucial in shaping forest ecosystems. In contrast, Dim.2 emphasized the importance of stand volume and structure, indicating that denser and more complex forests are linked to specific ecological outcomes. Dim.3 revealed that regeneration areas significantly contribute to biodiversity, while steeper slopes might hinder regeneration.
The analysis of the relationship between the aridity index and the elevation in various forest species highlights how environmental factors impact tree growth and forest management (Figure 6). Fir and beech prefer higher elevation and more humid conditions, showing optimal growth and greater volumes, indicating their sensitivity to aridity and role as indicators of forest health. Conversely, sessile oak and hornbeam exhibit resilience to increased aridity at lower elevations, maintaining significant tree volumes despite drier conditions. This adaptability underscores their importance in ecosystems facing climate change, suggesting their potential value in afforestation and reforestation initiatives.
About the relationship between tree regeneration (understory) with elevation (Figure 7), species composition, vitality, and the area occupied by the understory relative to the total management unit area, it was observed that at higher elevations, fir shows strong regeneration, occupying significant portions of the understory and exhibiting high vitality, indicating its preference for cooler, moist conditions. Spruce also regenerates successfully at mid to high elevations, where it occupies substantial areas and demonstrates moderate to high vitality. Both species appear well adapted to higher elevation environments, thriving in larger quantities and with greater health in these regions.
Beech trees occur at a wide range of elevations, showing strong vitality and occupying large areas. Their resilience and adaptability are evident in their constant presence under different ecological conditions. These conditions refer to their resilience and adaptability, their robustness across varying environments, their capacity to thrive in diverse conditions, and their ecological flexibility; this is demonstrated by their constant presence across a range of ecological conditions, highlighting their remarkable ability to persist. With a regeneration cover ranging from 0.0 to 7.5 (percent area × 100), beech’s ability to survive in diverse environments emphasizes its versatility and robustness as a species. Hornbeam and sessile oak occupy smaller areas of the understory, especially at low and mid elevations, as indicated by lower cover values. This limited presence may be influenced by their specific ecological niches and the suitability of site conditions for their growth. Although our analysis does not directly address vitality, the low understory cover suggests that these species may face more constraints in regeneration compared to others, such as beech, which exhibit wider adaptability at different elevations. Hardwood species as a group occupy varied areas and show moderate regeneration success, but they tend to perform better in lower to mid-elevation ranges.
Overall, the analysis suggests that fir, beech, and spruce regenerate more vigorously, occupy larger areas, and maintain higher vitality compared to hornbeam and sessile oak, which face more challenging conditions that limit their regeneration capacity.

4. Discussion

The R10mm trend analysis identified statistically significant changes in heavy rainfall days primarily in regions like the Western Carpathians and eastern Romania, suggesting localized climate impacts due to geographical and topographical factors. This highlights the need for adaptive forest management strategies that are region-specific [42,54,55]. At the same time, these patterns align with global observations where climate change intensifies forest ecosystem disruptions [2,56]. In Romania, species like beech and spruce face growing drought stress [23,24], consistent with studies linking extreme weather to mortality and regeneration decline.
The increasing trend in warm-wave days across much of Romania [39], especially in the western parts, poses serious implications for forest productivity [55,57]. Prolonged heat waves can exacerbate drought stress, increase tree mortality, and alter species composition. Although certain species like fir, beech, and spruce display a degree of resilience to climate impacts [23,58,59], it is essential to integrate climate-resilient management practices to safeguard forest health in the long term [60,61].

4.1. The Interaction Between Environmental and Ecological Parameters

The findings from this study underline the effects of climate change on Romania’s forest ecosystems, with particular emphasis on factors such as elevation, precipitation, aridity index, and their relationships with forest structural characteristics, like stand volume, species composition, and regeneration capacity.
Further analysis, particularly through correlation matrices, revealed strong positive relationships between elevation, precipitation, and the aridity index. Higher elevations tend to receive more rainfall, contributing to healthier forest conditions [5,62]. Additionally, soil litter and forest regeneration areas are positively correlated with stand structure [63], underscoring the importance of organic matter in promoting regeneration and biodiversity [64,65]. While elevation buffers climate impacts, prolonged heatwaves (WSDI trends) may exceed physiological limits for even resilient species like fir, as seen in lowland diebacks. Central European studies similarly note topography’s role in moderating forest vulnerability [55].

4.2. Characterization of Analyzed Management Units

The constant presence of these forests under diverse ecological conditions emphasizes their natural resilience and adaptability [66,67]. This capacity for persistence, reflected in their robustness in different environments, their ability to thrive under diverse conditions, and their ecological flexibility, suggests a significant potential for long-term survival despite environmental heterogeneity [68].
Our findings align with broader European studies of forest climate resilience, particularly in regions facing similar climatic stressors [69,70]. For example, the increasing exposure to heat waves in Romania mirrors trends observed in Central European beech forests, where rising temperatures have led to growth suppression and increased mortality rates. This broader context emphasizes the regional relevance of our study and highlights the common challenges facing temperate forests in the context of climate change [71].

4.3. Precipitation and Temperature Trends in Romania

The R10mm trend analysis revealed statistically significant changes on high precipitation days, particularly in regions such as the Western Carpathians and eastern Romania. These localized patterns suggest that geographic and topographic factors play a key role in shaping climate impacts, necessitating adaptive forest management strategies tailored to specific regions [42]. For example, areas experiencing an increase in heavy precipitation may require enhanced measures to mitigate soil erosion and manage water drainage, while regions with extended periods of drought may require strategies to improve drought resilience.
The increasing trend in the number of days with heat waves in most parts of Romania, especially in the western part, represents a significant challenge for forest productivity. Extended heat waves can potentially exacerbate drought stress, increase tree mortality rates, and cause changes in species composition. While certain species, such as fir, beech and spruce, show some degree of resilience to these climatic impacts, the long-term health of forest ecosystems will depend on the adoption of climate-resilient management practices. These practices may include promoting mixed-species stands, improving water-holding capacities, and prioritizing the regeneration of drought-tolerant species [61].
Correlation matrix analysis further reinforced the importance of the availability of moisture for forest stability, revealing strong positive relationships between elevation, precipitation, and aridity index. Higher elevations, which typically receive more precipitation, were associated with healthier forest conditions [5,62]. This finding aligns with PCA results, which identified precipitation and elevation as the main drivers of forest resilience in Romania. Furthermore, the positive correlations between soil litter, forest regeneration zones, and stand structure emphasize the essential role of organic matter in supporting regeneration and maintaining biodiversity [63,64,65]. These observations emphasize the need to maintain soil health and organic matter as part of sustainable forest management practices.

4.4. Limitations and Future Directions

Four key limitations qualify these insights: First, our 10-year data (2013–2022) may miss long-term shifts like species migration [32]. Second, unmeasured pressures (logging, tourism) could interact with climate stressors. Third, correlations between aridity and tree health need experimental validation. Finally, regional trends may mask microsite variations [42].
While resilience indicators suggest relative stability in some species and regions, increasing trends in heat waves (WSDI) and extreme precipitation (R10mm) highlight emerging risks that could accelerate forest stress in the next decades. Despite current stability, escalating heatwaves and precipitation shifts threaten ecosystem services like carbon sequestration. Future studies should evaluate genetic resilience and socio-economic impacts to guide policy [17]. The study concludes that, despite current minimal changes in the state of forest ecosystems in Romania, proactive measures are essential to mitigate the potential impacts of climate change. By integrating specific regional strategies and prioritizing climate resilient practices, forest managers can better protect the long-term health and productivity of Romania’s forests.

5. Conclusions

This research study provides crucial insights into how climate change is affecting Romanian forests, highlighting their resilience and vulnerabilities by integrating climate indicators with forest responses across 13 experimental forest districts from 2013–2022.
Key findings include an analysis of climate data (1950–2022) showing varied R10mm trends (heavy rainfall days) from −1.4 to 1.8 days per decade, with significant changes observed in eastern Romania and the Western Carpathians. The warm spell duration index (WSDI) also indicates an increase in warm spells, particularly in western regions, at approximately 2 days per decade. Strong correlations were found between elevation and precipitation (r = 0.615), with principal component analysis (PCA) identifying these as primary drivers of forest resilience, explaining 56.7% of the variance. Regarding species-specific responses, fir, beech, and spruce exhibit strong climate resilience with healthy regeneration across various conditions, whereas sessile oak and hornbeam face greater challenges due to changing aridity patterns. Furthermore, increased precipitation positively correlated with soil litter and stand structure, suggesting moisture enhances soil fertility and supports complex ecosystems, while diverse forests also foster natural regeneration.
These implications for forest management stem from this study, which offers the first comprehensive assessment of climate–forest interactions in Romanian ecosystems by combining long-term management data with climate trends. The findings emphasize the importance of elevation-precipitation gradients as key indicators of resilience. This information offers practical guidance for forest managers to protect resilient species while supporting vulnerable ones facing environmental pressures. As climate change intensifies, these results will aid in developing adaptive forest management strategies and long-term plans to safeguard the health and productivity of Romanian forests, ensuring their continued provision of essential ecosystem services for future generations.

Author Contributions

Conceptualization, S.C., D.P., L.M., and O.B.; Formal analysis, A.C.D.; Investigation, D.P., L.M., and Ș.L.; Methodology, S.C., L.M., and Ș.L.; Software, A.C.D.; Supervision, O.B.; Validation, A.C.D. and Ș.L.; Writing—original draft, S.C., D.P., and L.M.; Writing—review and editing, S.C., D.P., A.C.D., Ș.L., and O.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study was conducted under the projects PN23090202 and PN23090101 within FORCLIMSOC Nucleus Program (Contract No. 12N/2023), a grant from the Romanian Ministry of Research and Innovation.

Data Availability Statement

Datasets are available on request from the authors.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Forests 16 00941 g001
Figure 1. Map showing Romania at European level (right upper panel) and research area locations marked with red dots (main panel).
Figure 1. Map showing Romania at European level (right upper panel) and research area locations marked with red dots (main panel).
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Figure 2. The number of days per decade with changes in R10mm. The scale indicates negative trends in blue, no trends in yellow, and positive trends in red. The white dot inside each grid pixel represents the computed statistically significant trend for p < 0.05.
Figure 2. The number of days per decade with changes in R10mm. The scale indicates negative trends in blue, no trends in yellow, and positive trends in red. The white dot inside each grid pixel represents the computed statistically significant trend for p < 0.05.
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Figure 3. The number of days per decade with changes in warm spell duration index. The scale indicates small trends in dark blue and increased positive trends in red. The white dot inside each grid pixel represents a statistically significant trend calculated for p < 0.05.
Figure 3. The number of days per decade with changes in warm spell duration index. The scale indicates small trends in dark blue and increased positive trends in red. The white dot inside each grid pixel represents a statistically significant trend calculated for p < 0.05.
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Figure 4. Correlation matrix of environmental and ecological variables.
Figure 4. Correlation matrix of environmental and ecological variables.
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Figure 5. Principal component analysis of environmental and ecological variables.
Figure 5. Principal component analysis of environmental and ecological variables.
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Figure 6. Relationship between the aridity index and elevation.
Figure 6. Relationship between the aridity index and elevation.
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Figure 7. Relationship between tree regeneration (understory) with elevation.
Figure 7. Relationship between tree regeneration (understory) with elevation.
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Table 1. Environmental characteristics of forest districts.
Table 1. Environmental characteristics of forest districts.
Forest DistrictsCodeArea [ha]Alt [m]Inc [°]P [mm]No. of uaMain SpeciesClimatic Zone
Craiova16091975<553414Quercus spp.Continental
Baragan400233351<5452302Quercus spp.Steppic
Tomnatec4004724487422696717Picea abiesAlpin
Hemeius400648170<550932Various HardwoodContinental
Mihaesti40078445541175651586Fagus sylvaticaContinental
Stefanesti401048189<5568181Quercus spp.Continental
Sacele40122485103727631245Picea abiesAlpin
Lechinta4013226242617558467Various HardwoodContinental
Caransebes401417,735560317111377Fagus sylvaticaAlpin
Mures40151793841352845Quercus spp.Continental
Timisoara4016156181<553863Various HardwoodContinental
Tulcea4022475151<540034Quercus spp.Steppic
Vidra40238469430275161402Fagus sylvaticaAlpin
Alt—elevation; Inc—mean slope; ua—management planning unit.
Table 2. Descriptive statistics of variables within research area.
Table 2. Descriptive statistics of variables within research area.
VariableMinimumMaximumAverageStandard
Deviation of (s)		Variance
(s2)		Coefficient of Variance
(s %)
Slope (°)06021.811.55134.2953
Elevation (m)491550556261.3768,317.3447
Soil litter (Classes 1–4)1430.740.5524
Stand structure (Classes 1–4)1420.810.6437
Stand volume (m3)07118597.239454.16114
Mean precipitations (mm/year)399.97802.73605.9989.137944.7315
Aridity index (no unit)0.441.080.870.170.0319
Species (number)11664.2918.4669
Regeneration_area (% surface)090.701.632.67232
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Chivulescu, S.; Pitar, D.; Dobre, A.C.; Mărmureanu, L.; Leca, Ș.; Badea, O. Quantifying Climate Change Impacts on Romanian Forests: Indicators of Resilience and Vulnerability. Forests 2025, 16, 941. https://doi.org/10.3390/f16060941

AMA Style

Chivulescu S, Pitar D, Dobre AC, Mărmureanu L, Leca Ș, Badea O. Quantifying Climate Change Impacts on Romanian Forests: Indicators of Resilience and Vulnerability. Forests. 2025; 16(6):941. https://doi.org/10.3390/f16060941

Chicago/Turabian Style

Chivulescu, Serban, Diana Pitar, Alexandru Claudiu Dobre, Luminița Mărmureanu, Ștefan Leca, and Ovidiu Badea. 2025. "Quantifying Climate Change Impacts on Romanian Forests: Indicators of Resilience and Vulnerability" Forests 16, no. 6: 941. https://doi.org/10.3390/f16060941

APA Style

Chivulescu, S., Pitar, D., Dobre, A. C., Mărmureanu, L., Leca, Ș., & Badea, O. (2025). Quantifying Climate Change Impacts on Romanian Forests: Indicators of Resilience and Vulnerability. Forests, 16(6), 941. https://doi.org/10.3390/f16060941

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