Extreme warm temperatures alter forest phenology and productivity in Europe

Detection and attribution of the start of the growing season changes in the Northern Hemisphere

Global climate change has led to significant changes in land surface phenology. At present, research on the factors influencing the start of the growing season (SOS) mainly focuses on single factor effects, such as temperature and precipitation, ignoring the combined action of multiple factors. The impact of multiple factors on the spatial and temporal patterns of the SOS in the Northern Hemisphere is not clear, and it is necessary to combine multiple factors to quantify the degrees of influence of different factors on the SOS. Based on the GIMMS3g NDVI dataset, CRU climate data and other factor data, we used geographic detector model, random forest regression model, multiple linear regression, partial correlation analysis and Sen + Mann-Kendall trend analysis to explore the variation of the SOS in the Northern Hemisphere to reveal the main driving factors and impact threshold of 17 influencing factors on the SOS. The results showed that (1) during the past 34 years (1982-2015), the SOS in Europe and Asia mainly showed an advancing trend, whereas the SOS in North America mainly showed a delaying trend. (2) The SOS was mainly controlled by frost frequency, temperature and humidity. Increasing frost frequency inhibited the advancement of the SOS, and increasing temperature and humidity promoted the advancement of the SOS. (3) There were thresholds for the influences of the driving factors on the SOS. Outside the threshold ranges, the response mechanism of the SOS to driving factors changed. The results are important for understanding the response of the SOS to global climate change.

Heterogeneous responses of wetland vegetation to climate change in the Amur River basin characterized by normalized difference vegetation index from 1982 to 2020

Climate change affects wetland vegetation dramatically in mid- and high- latitudes, especially in the Amur River basin (ARB), straddling three countries and distributing abundance wetlands. In this study, spatiotemporal changes in average normalized difference vegetation index (NDVI) of wetland during the annual growing season were examined in the ARB from 1982 to 2020, and the responses of wetland vegetation to climatic change (temperature and precipitation) in different countries, geographic gradients, and time periods were analyzed by correlation analysis. The NDVI of wetland in the ARB increased significantly (p < 0.01) at the rate of 0.023 per decade from 1982 to 2020, and the NDVI on the Russian side (0.03 per decade) increased faster than that on the Chinese side (0.02 per decade). The NDVI of wetland was significantly positively correlated with daily mean temperature (p < 0.05, r = 0.701) and negatively correlated with precipitation, although the correlation was not significant (p > 0.05, r = -0.12). However, the asymmetric effects of diurnal warming on wetland vegetation were weak in the ARB. Correlations between the NDVI of wetland and climatic factors were zonal in latitudinal and longitudinal directions, and 49°N and 130°E were the points for a shift between increasing and decreasing correlation coefficients, closely related to the climatic zone. Under climate warming scenarios, the NDVI of wetland is predicted to continue to increase until 2080. The findings of this study are expected to deepen the understanding on response of wetland ecosystem to global change and promote regional wetland ecological protection.

Modeling the effect of adaptation to future climate change on spring phenological trend of European beech (Fagus sylvatica L.)

Temperate trees could cope with climate change through phenotypic plasticity of phenological key events or adaptation in situ via selection on genetic variation. However, the relative contribution of local adaptation and phenotypic plasticity to phenological change is unclear for many ecologically important tree species. Here, we analyzed the leaf-out data of European beech (Fagus sylvatica L.) from 50 provenances planted in 7 trial sites. We first constructed a function between chilling accumulation (CA) and photoperiod-associated heat requirement (PHR) of leaf-out date for each provenance and quantified the relationship between parameters of the CA-PHR function and climatic variables at provenance origins by using the random forest model. Furthermore, we used the provenance-specific CA-PHR function to simulate future leaf-out dates under two climate change scenarios (RCP 4.5 and 8.5) and two assumptions (no adaptation and adaptation). The results showed that both CA, provenance, and their interactions affected the PHR of leaf-out. The provenances from southeastern Europe exhibited a stronger response of PHR to CA and thus flushed earlier than northwestern provenances. The parameters of the CA-PHR function were connected with climatic variables (e.g., mean diurnal temperature range, temperature seasonality) at the originating sites of each provenance. If only considering the phenotypic plasticity, the leaf-out date of European beech in 2070-2099 will advance by 6.8 and 9.0 days on average relative to 1951-2020 under RCP 4.5 and RCP 8.5, respectively. However, if F. sylvatica adapts to future climate change by adopting the current strategy, the advance of the leaf-out date will weaken by 1.4 and 3.4 days under RCP 4.5 and RCP 8.5, respectively. Our results suggest that the European beech could slow down its spring phenological advances and reduce its spring frost risk if it adopts the current strategy to adapt to future climate change.

Response of plant functional traits to nitrogen enrichment under climate change: A meta-analysis

Soil nitrogen (N) supply is essential in influencing plant functional traits and regulating plant morphological and physiological performances. The effects of N on plants can be altered by complex environmental changes. However, conflicting results have been reported on the co-effects of N and climatic variables on plant performance, which may be attributed to differences in experiment setting and approach, e.g., ecosystem, duration, plant type, and fertilizer form. To elucidate the general response of plant performance to increasing soil N availability under climate change, a global meta-analysis was conducted to synthesize 380 publications studying interactions of N enrichment and four climatic variables (e.g., elevated atmospheric CO₂ (eCO₂), drought, precipitation, and warming) on performance-related traits (e.g., size, nutrient, and fitness). Results showed that N enrichment increased shoot and root size, nutrient, and fitness of terrestrial plants. The synergistic interactions of N × eCO₂ and antagonistic interactions of N × drought were found on plant overall performance (mainly on plant size), indicating that the N effects can be aggregated by eCO₂ and mitigated by drought. The co-effects of N and climatic variables on plant overall performance rely on experiment approach, duration, ecosystem type, or plant functional type. Synergistic interactions of N × eCO₂ and antagonistic interactions of N × drought, N × precipitation, and N × warming on plant overall performance were found mainly in greenhouse experiments and short-term experiments (duration ≤ one year), but not in the field or longer-term experiments. The results highlighted that N effects on plant performance were not isolated, but can be modified by climate changes. These findings can improve the future modeling predictions of plant performance under complex climate change and provide a fundamental basis for N management strategies to optimize plant performance in production, N nutrient, and reproduction while enabling sustainability of plant production systems.

Spring and Autumn Phenology in Sessile Oak (Quercus petraea) Near the Eastern Limit of Its Distribution Range

Due to the visible and predictable influence of climate change on species’ spatial distributions, the conservation of marginal peripheral populations has become topical in forestry research. This study aimed to assess the spring (budburst, leaf development, and flowering) and autumn (leaf senescence) phenology of sessile oak (Quercus petraea), a species widespread across European forests close to its ranges’ eastern limit. This study was performed in Romania between spring 2017 and 2020, and it included a transect with three low-altitude populations, a reference population from its inner range, and a sessile oak comparative trial. The temperature was recorded to relate changes to phenophase dynamics. We identified small variations between the reference and peripheral populations associated with climatic conditions. In the peripheral populations, budburst timing had day-of-year (DOY) values <100, suggesting that sessile oak may be more susceptible to late spring frost. Furthermore, we found spring phenophase timing to be more constant than autumn senescence. Moreover, budburst in the sessile oak comparative trial had obvious longitudinal tendencies, with an east to west delay of 0.5–1.4 days per degree. In addition, budburst timing influenced leaf development and flowering, but not the onset of leaf senescence. These findings improve our understanding of the relationship between spring and autumn phenophase dynamics and enhance conservation strategies regarding sessile oak genetic resources.

Grassland Phenology’s Sensitivity to Extreme Climate Indices in the Sichuan Province, Western China

Depending on the vegetation type, extreme climate and drought events have a greater impact on the end of the season (EOS) and start of the season (SOS). This study investigated the spatial and temporal distribution characteristics of grassland phenology and its responses to seasonal and extreme climate changes in Sichuan Province from 2001 to 2020. Based on the data from 38 meteorological stations in Sichuan Province, this study calculated the 15 extreme climate indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The results showed that SOS was concentrated in mid-March to mid-May (80–140 d), and 61.83% of the area showed a significant advancing trend, with a rate of 0–1.5 d/a. The EOS was concentrated between 270–330 d, from late September to late November, and 71.32% showed a delayed trend. SOS was strongly influenced by the diurnal temperature range (DTR), yearly maximum consecutive five-day precipitation (RX5), and the temperature vegetation dryness index (TVDI), while EOS was most influenced by the yearly minimum daily temperature (TNN), yearly mean temperature (TEMP_MEAN), and TVDI. The RX5 day index showed an overall positive sensitivity coefficient for SOS. TNN index showed a positive sensitivity coefficient for EOS. TVDI showed positive and negative sensitivities for SOS and EOS, respectively. This suggests that extreme climate change, if it causes an increase in vegetation SOS, may also cause an increase in vegetation EOS. This research can provide a scientific basis for developing regional vegetation restoration and disaster prediction strategies in Sichuan Province.

The Sensitivity of Vegetation Phenology to Extreme Climate Indices in the Loess Plateau, China

Climate changes, especially increased temperatures, and precipitation changes, have significant impacts on vegetation phenology. However, the response of vegetation phenology to the extreme climate in the Loess Plateau in Northwest China remains poorly quantified. The research described here analyzed the spatial change in vegetation phenology and the response of vegetation phenology to climate change in the Loess Plateau from 2001 to 2018, using data from seven extreme climate indices based on the ridge regression method. The results showed that extreme climate indexes, TNn (yearly minimum value of the daily minimum temperature), TXx (yearly maximum value of the daily maximum temperature), and RX5day (yearly maximum consecutive five-day precipitation) progressively increased from 2001 to 2018 in the Loess Plateau region, but decrease trend was found in DRT (diurnal temperature range). The start of the growing season (SOS) of vegetation gradually advanced with precipitation from northwest to southeast, and the rate was +0.38 d/a. The overall vegetation end of the growing season (EOS) was delayed, and the trend was −2.83 d/a. The sensitivity of the different vegetation phenology to different extreme weather indices showed obvious spatial differences, the sensitivity coefficient of SOS being mainly positive in the region, whereas the sensitivity coefficient of EOS was negative generally. More sensitivity was found in the EOS to extreme climate indexes than in the SOS. Forest, shrubland and grassland have similar responses to DRT and TNn; namely, both SOS and EOS are advanced with the increase in DRT and delayed with the increase in TNn (the sensitivity coefficient is quite different) but have different responses to RX5day and TXx. These results reveal that extreme climate events have a greater impact on vegetation EOS than on vegetation SOS, with these effects varying with vegetation types. This research can provide a scientific basis for formulating a scientific basis for regional vegetation restoration strategies and disaster prediction on the Loess Plateau.

December-March temperature reconstruction from tree-ring earlywood width in southeastern China during the period of 1871-2016

Extremely cold temperatures are a significant threat to agriculture and transportation in winter in southeastern China. However, due to the shortness of instrumental records and the scarcity of long-term temperature reconstructions, more high-quality temperature reconstructions are still needed to fully examine their spatial-temporal variability over the past several centuries. In this study, we built an earlywood width (EWW) chronology, a latewood width (LWW) chronology, and a tree-ring width (TRW) chronology using tree-ring samples of Pinus taiwanensis Hayata from the western Tianmu Mountains and the Xianyu Mountains in southeastern China. The tree growth-climate relationships were analyzed, and we found the strongest correlation between December and March mean temperature and the EWW chronology. The December-March mean temperature history was then reconstructed over the period of 1871-2016 using a linear regression model, which is the first EWW-based temperature reconstruction in southeastern China. With a higher explained variance (47.0%) than that (31.7%) of a previous reconstruction using a TRW chronology, the quality of the model has largely improved. This reconstruction was also comparable with other nearby records, further demonstrating the reliability of our new model. Furthermore, our reconstruction exhibits a significantly negative relationship with the East Asian winter monsoon index (EAWMI) since the 1920s, which may be attributed to the obviously enhanced EAWMI thereafter.

Warm nights drive Coffea arabica ripening in Tanzania

Studies have demonstrated that plant phenophases (e.g. budburst, flowering, ripening) are occurring increasingly earlier in the season across diverse ecologies globally. Despite much interest that climate change impacts have on coffee (Coffea arabica), relatively little is known about the driving factors determining its phenophases. Using high-resolution microclimatic data, this study provides initial insights on how climate change is impacting C. arabica phenophases in Tanzania. In particular, we use generalized additive models to show how warming nocturnal temperatures (T_night), as opposed to day-time or maximum temperatures, have a superseding effect on the ripening of coffee and subsequent timing of harvest. A warm night index (WNI), generated from mean nocturnal temperature, permits accurate prediction of the start of the harvest season, which is superior to existing methods using growing degree days (GDD). The non-linear function indicates that a WNI of 15 °C is associated with the latest ripening coffee cherries (adjusted R² = 0.95). As the WNI increases past the inflection point of ~ 16 °C, ripening occurs earlier and progresses more or less linearly at a rate of ~ 17 ± 1.95 days for every 1 °C increase in WNI. Using the WNI will thus not only allow farmers to more accurately predict their harvest start date, but also assist with identifying the most suitable adaptation strategies which may reduce harvest-related costs and buffer potential losses in quality and production.

Impacts of preseason drought on vegetation spring phenology across the Northeast China Transect

Vegetation phenology is undergoing profound changes in response to the recent increases in the intensity and frequency of drought events. However, the mechanisms by which drought affects the start of the growing season (SGS) are poorly understood particularly in arid and semi-arid regions. Here, we identified varying degrees of preseason drought events and analyzed the sensitivity of the SGS to preseason drought across the Northeast China Transect (NECT). Our results showed that drought caused a delayed SGS in grassland ecosystems, but an advanced SGS within forest ecosystems. These contrasting responses to preseason drought reflected different adaptive strategies between vegetation types. The SGS was shown to be highly sensitive to short timescales drought (1-3 months) in semi-arid grasslands where annual precipitation is 200-300 mm (i.e. SAGE_200-300). Biomes within this region were found to be most vulnerable out of all the ecosystems to drought. Given the frequent nature of droughts in the mid-latitudes, a drought early warning system was recommended accompanied by improved modeling of how the SGS will be affected by intensified drought under future climate change.

A comparison of ground-based methods for obtaining large-scale, high-resolution data on the spring leaf phenology of temperate tree species

Phenological variation in spring leafing between and within species can determine plant responses to warmer winter and spring temperatures in the short term. Methods are needed for monitoring canopy development that can be replicated on a large-scale, while retaining fine-scale resolution at the level of individual trees. Citizen science has the potential to provide this, but a range of approaches exist in terms of the phenophase recorded (e.g. budburst or leaf expansion), how the phenophase is characterised (first events or intensity monitoring) and the portion of tree crown assessed and observation frequency. A comparison of spring budburst and leaf expansion of four tree species (Fraxinus excelsior, Fagus sylvatica, Quercus robur and Acer pseudoplatanus) was monitored in one woodland using (1) counts of expanded leaves on three crown sections, (2) percentage estimates of expanded leaves across the whole crown and (3) a greenness index from photography. Logistic growth models were applied to make comparisons. First-event dates were found to be misleading due to high variation in leaf development rates within and between species. Percentage estimates and counts produced similar estimates of leaf expansion timing and rate. The greenness index produced similar estimates of timing, but not rate, and was compromised by practicalities of photographing individual crowns in closed-canopy woodland. Citizen scientists could collect data across the period of spring leafing, with visual counts and/or estimates made every 3-4 days, subject to tests of reliability in pilot citizen science studies.

Extreme Temperature Events during 1960–2017 in the Arid Region of Northwest China: Spatiotemporal Dynamics and Associated Large-Scale Atmospheric Circulation

Studying the dynamic changes of extreme temperatures and associated large-scale atmospheric circulation is important for predicting the occurrence of extreme temperatures and reducing their adverse impact and damage. Based on the surface temperature data sets collected from 87 weather stations over the arid region of Northwest China (ARNC) during 1960–2017, the Sen’s slope estimator, Mann–Kendall test, Cumulative anomaly, Moving t-test, and Synthetic analysis methods were used to analyze the spatiotemporal dynamics and breaking-point change characteristics of extreme temperatures, and to discuss its associated large-scale atmospheric circulation. The results revealed that at the temporal scale, summer days (SU25), warm days (TX90p), warm nights (TN90p), and warm spell duration indicator (WSDI) showed a remarkable increasing trend at the rates of 2.27, 1.49, 3, and 2.28 days/decade, respectively. The frost days (FD), cold days (TX10p), cold nights (TN10p), and cold spell duration indicator (CSDI) significantly decreased at the rates of −3.71, −0.86, −1.77, and −0.76 days/decade, respectively, during the study period. Spatially, the warming trend in the study area is very obvious as a whole, despite pronounced spatial differences in warming rate. After the breakpoint years, the frequency and probability distribution for extreme warm and cold indices were all inclined to the hotter part of the density distribution. This indicates that the climate over the study region shifted sharply and tended to be warmer. The analysis of large-scale atmospheric circulation indicates that the warming trend in the arid region of Northwest China (ARNC) is positively correlated with geopotential height at 500 hPa and negatively correlated with total cloudiness. The findings from this study have important implications for forecasting extreme temperature events and mitigating the impacts of climatological disasters in this region.

Forest Phenology Dynamics to Climate Change and Topography in a Geographic and Climate Transition Zone: The Qinling Mountains in Central China

Forest ecosystems in an ecotone and their dynamics to climate change are growing ecological and environmental concerns. Phenology is one of the most critical biological indicators of climate change impacts on forest dynamics. In this study, we estimated and visualized the spatiotemporal patterns of forest phenology from 2001 to 2017 in the Qinling Mountains (QMs) based on the enhanced vegetation index (EVI) from MODerate-resolution Imaging Spectroradiometer (MODIS). We further analyzed this data to reveal the impacts of climate change and topography on the start of the growing season (SOS), end of the growing season (EOS), and the length of growing season (LOS). Our results showed that forest phenology metrics were very sensitive to changes in elevation, with a 2.4 days delayed SOS, 1.4 days advanced EOS, and 3.8 days shortened LOS for every 100 m increase in altitude. During the study period, on average, SOS advanced by 0.13 days year−1, EOS was delayed by 0.22 days year−1, and LOS increased by 0.35 day year−1. The phenological advanced and delayed speed across different elevation is not consistent. The speed of elevation-induced advanced SOS increased slightly with elevation, and the speed of elevation-induced delayed EOS shift reached a maximum value of 1500 m from 2001 to 2017. The sensitivity of SOS and EOS to preseason temperature displays that an increase of 1 °C in the regionally averaged preseason temperature would advance the average SOS by 1.23 days and delay the average EOS by 0.72 days, respectively. This study improved our understanding of the recent variability of forest phenology in mountain ecotones and explored the correlation between forest phenology and climate variables in the context of the ongoing climate warming.

Exploring the Sensitivity of Subtropical Stand Aboveground Productivity to Local and Regional Climate Signals in South China

Subtropical forest productivity is significantly affected by both natural disturbances (local and regional climate changes) and anthropogenic activities (harvesting and planting). Monthly measures of forest aboveground productivity from natural forests (primary and secondary forests) and plantations (mixed and single-species forests) were developed to explore the sensitivity of subtropical mountain productivity to the fluctuating characteristics of climate change in South China, spanning the 35-year period from 1981 to 2015. Statistical analysis showed that climate regulation differed across different forest types. The monthly average maximum temperature, precipitation, and streamflow were positively correlated with primary and mixed-forest aboveground net primary productivity (ANPP) and its components: Wood productivity (WP) and canopy productivity (CP). However, the monthly average maximum temperature, precipitation, and streamflow were negatively correlated with secondary and single-species forest ANPP and its components. The number of dry days and minimum temperature were positively associated with secondary and single-species forest productivity, but inversely associated with primary and mixed forest productivity. The multivariate ENSO (EI Niño-Southern Oscillation) index (MEI), computed based on sea level pressure, surface temperature, surface air temperature, and cloudiness over the tropical Pacific Ocean, was significantly correlated with local monthly maximum and minimum temperatures (Tmax and Tmin), precipitation (PRE), streamflow (FLO), and the number of dry days (DD), as well as the monthly means of primary and mixed forest aboveground productivity. In particular, the mean maximum temperature increased by 2.5, 0.9, 6.5, and 0.9 °C, and the total forest aboveground productivity decreased by an average of 5.7%, 3.0%, 2.4%, and 7.8% in response to the increased extreme high temperatures and drought events during the 1986/1988, 1997/1998, 2006/2007, and 2009/2010 EI Niño periods, respectively. Subsequently, the total aboveground productivity values increased by an average of 1.1%, 3.0%, 0.3%, and 8.6% because of lagged effects after the wet La Niña periods. The main conclusions of this study demonstrated that the influence of local and regional climatic fluctuations on subtropical forest productivity significantly differed across different forests, and community position and plant diversity differences among different forest types may prevent the uniform response of subtropical mountain aboveground productivity to regional climate anomalies. Therefore, these findings may be useful for forecasting climate-induced variation in forest aboveground productivity as well as for selecting tree species for planting in reforestation practices.

Dynamics of vegetation autumn phenology and its response to multiple environmental factors from 1982 to 2012 on Qinghai-Tibetan Plateau in China

Autumn phenological shifts induced by environmental change have resulted in substantial impacts on ecosystem processes. However, autumn phenology and its multiple related controlling factors have not been well studied. In this study, the spatiotemporal patterns of the end date of the vegetation growing season (EGS) and their multiple controls (climate change, summer vegetation growth and human activities) over the Qinghai-Tibetan Plateau (QTP) were investigated using the satellite-derived normalized difference vegetation index (NDVI) based on GIMMS3g datasets during 1982-2012. The results showed that there was no significant temporal trend in the EGS during the period of 1982-2012. Spatially, there was a notable advancing trend in the southwest region and a delayed trend in the other regions of the QTP during 1982-2000, and this spatial trend was reversed during 2001-2012. We found average temperature, precipitation and sunshine duration of autumn exerted positive effects on EGS on the QTP, while average temperature and sunshine duration of summer exerted negative effects. Our results indicated that vegetation growth in summer tends to induce an earlier EGS in alpine vegetation, whereas summer vegetation degradation could delay the EGS on the QTP. In contrast, moderate grazing delays vegetation browning in autumn, while overgrazing leads to advancement of grass senescence. This study improves our understanding of how multiple environmental variables jointly affect autumn phenology and highlights the importance of biotic controls for autumn phenology on the QTP.

Monthly and annual temperature extremes and their changes on the Tibetan Plateau and its surroundings during 1963-2015

In this study, the spatiotemporal distributions of monthly and annual temperature minima (T_min) and maxima (T_max), extreme T_min and T_max, the highest (lowest) T_min (T_max), frost day (FD), icing day (ID), summer day (SD) and tropical night (TR) at 112 stations and over the ten large river basins on the Tibetan Plateau and its surroundings (TPS) during 1963–2015 are examined. Mann-Kendall test is applied for the trends. The analyses show: the northwest experiences the hottest summer while the central TPS has the coldest winter and most frequent frost and icing days. The northwest (southeast) features the highest (lowest) monthly extreme temperature ranges. The northwest has the most frequent hot summer days, whereas the southeast has the least frequent frost and icing days. The entire TPS displays few tropical nights. Most stations show positive trends for all monthly and annual T_min and T_max variables. February displays the most positive trends for both monthly T_min and T_max variables while April shows the highest number of stations with decreasing trends in monthly T_max. The trends of FD and ID are negative, whereas the trends of SU and TR are positive. Over river basins, the trends of monthly T_min are all positive and statistically significant and the trends of monthly T_max are all positive except for one negative trend and around 1/3 of the positive trends are statistically significant. Relatively larger increases in monthly T_min and T_max are noted for the cold season than the warm. The monthly and annual T_min variables increase more than T_max variables.

Pan European Phenological database (PEP725): a single point of access for European data

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Forest Soil Bacteria: Diversity, Involvement in Ecosystem Processes, and Response to Global Change

The ecology of forest soils is an important field of research due to the role of forests as carbon sinks. Consequently, a significant amount of information has been accumulated concerning their ecology, especially for temperate and boreal forests. Although most studies have focused on fungi, forest soil bacteria also play important roles in this environment. In forest soils, bacteria inhabit multiple habitats with specific properties, including bulk soil, rhizosphere, litter, and deadwood habitats, where their communities are shaped by nutrient availability and biotic interactions. Bacteria contribute to a range of essential soil processes involved in the cycling of carbon, nitrogen, and phosphorus. They take part in the decomposition of dead plant biomass and are highly important for the decomposition of dead fungal mycelia. In rhizospheres of forest trees, bacteria interact with plant roots and mycorrhizal fungi as commensalists or mycorrhiza helpers. Bacteria also mediate multiple critical steps in the nitrogen cycle, including N fixation. Bacterial communities in forest soils respond to the effects of global change, such as climate warming, increased levels of carbon dioxide, or anthropogenic nitrogen deposition. This response, however, often reflects the specificities of each studied forest ecosystem, and it is still impossible to fully incorporate bacteria into predictive models. The understanding of bacterial ecology in forest soils has advanced dramatically in recent years, but it is still incomplete. The exact extent of the contribution of bacteria to forest ecosystem processes will be recognized only in the future, when the activities of all soil community members are studied simultaneously.