Forests

Assessing the potential for forest carbon (C) capture and storage requires accurate assessments of C in live tree tissues. In the vast majority of local, regional, and global assessments, C content has been assumed to be 50% of tree biomass; however, recent studies indicate that this assumption is not accurate, with substantial variation in C content among tree species as well as among tissue types. Here we conduct a comprehensive literature review to present a global synthesis of C content in tissues of live trees. We found a total of 253 species-specific stem wood C content records in 31 studies, and an additional 34 records of species with C content values of other tissues in addition to stem wood. In all biomes, wood C content varied widely across species ranging from 41.9–51.6% in tropical species, 45.7–60.7% in subtropical/Mediterranean species, and 43.4–55.6% in temperate/boreal species. Stem wood C content varied significantly as a function of biome and species type (conifer, angiosperm). Conifer species exhibited greater wood C content than angiosperm species (50.8 ± 0.7% (95% C.I.) and 47.7 ± 0.3%, respectively), a trend that was consistent among all biomes. Although studies have documented differences in C content among plant tissues, interspecific differences in stem wood appear to be of greater importance overall: among species, stem wood C content explained 37, 76, 48, 81, and 63% respectively of the variation in bark, branch, twig, coarse root, and fine root C content values, respectively. In each case, these intraspecific patterns approximated 1:1 linear relationships. Most published stem wood C content values (and all values for other tree tissues) are based on dried wood samples, and so neglect volatile C constituents that constitute on average 1.3–2.5% of total C in live wood. Capturing this volatile C fraction is an important methodological consideration for future studies. Our review, and associated data compilation, provides empirically supported wood C fractions that can be easily incorporated into forest C accounting, and may correct systematic errors of ~1.6–5.8% in forest C assessments.

The present study focused on how forests will be managed in the future in light of the increased emphasis being put by the public on the ecological and recreational values of forests, the trend towards an increased share of non-resident forest owners, and the increased female forest ownership. The value and belief basis of forest management attitudes was explored using a questionnaire sent to a sample of private forest owners ‘residing on’ (n = 995, return rate = 51.3%) and ‘not residing on’ the forest property (n = 997, return rate = 50%). The results showed that a share of private forest owners strongly value both the view that the forest should predominately be used for timber production and the view that preservation is most important. The proposed hierarchical structure of influence, in which the forest management attitude was influenced by values and beliefs, was supported in the study. The ecological, recreational, and production forest values primarily influenced the most closely related forest management attitude, even if some cross-sectional effects and some effects of socio-demographics were found, showing that the view a private forest owner has on different forms of management styles is shaped by the perceived multiple values of the forest.

Climate change significantly influences changes in ecological phenomena and processes, such as species distribution and phenology, thus accelerating the rate of species extinction or prosperity. Climate change is considered to be one of the most important threats to global biodiversity in the 21st century and will pose significant challenges to biodiversity conservation in the future. The use of niche modelling to predict changes in the suitable distribution of species under climate change scenarios is becoming a hot topic of biological conservation. In this study, we use data from China’s National Forest Continuous Inventory as well as specimen collection data of Cunninghamia lanceolata (Lamb.) Hook to run optimized Maxent models to predict potential suitable distribution of the species in the present day, 2050s, and 2070s under different climate change scenarios in China. In the modeling process, the most important uncorrelated variables were chosen, and the sample-size-adjusted Akaike information criterion (AICc) was used to select the optimal combination of feature type and regularization multiplier. Variable selection reduced the number of variables used and the complexity of the model, and the use of the AICc reduced overfitting. Variables relating to precipitation were more important than temperature variables in predicting C. lanceolata distribution in the optimal model. The predicted suitable distribution areas of C. lanceolata were different for the different periods under different climate change scenarios, with the centroids showing a degree of northward movement. The suitable distribution area is predicted to become more fragmented in the future. Our results reveal the climate conditions required for the suitable distribution of C. lanceolata in China and the likely changes to its distribution pattern in the future, providing a scientific basis for the sustainable management, protection, and restoration of the suitable habitat of this economically important tree species in the context of climate change.

The increase in aridity, mainly by decreases in precipitation but also by higher temperatures, is likely the main threat to the diversity and survival of Mediterranean forests. Changes in land use, including the abandonment of extensive crop activities, mainly in mountains and remote areas, and the increases in human settlements and demand for more resources with the resulting fragmentation of the landscape, hinder the establishment of appropriate management tools to protect Mediterranean forests and their provision of services and biodiversity. Experiments and observations indicate that if changes in climate, land use and other components of global change, such as pollution and overexploitation of resources, continue, the resilience of many forests will likely be exceeded, altering their structure and function and changing, mostly decreasing, their capacity to continue to provide their current services. A consistent assessment of the impacts of the changes, however, remains elusive due to the difficulty of obtaining simultaneous and complete data for all scales of the impacts in the same forests, areas and regions. We review the impacts of climate change and other components of global change and their interactions on the terrestrial forests of Mediterranean regions, with special attention to their impacts on ecosystem services. Management tools for counteracting the negative effects of global change on Mediterranean ecosystem- services are finally discussed.

Chilgoza pine is an economically and ecologically important evergreen coniferous tree species of the dry and rocky temperate zone, and a native of south Asia. This species is rated as near threatened (NT) by the International Union for Conservation of Nature (IUCN). This study hypothesized that climatic, soil and topographic variations strongly influence the distribution pattern and potential habitat suitability prediction of Chilgoza pine. Accordingly, this study was aimed to document the potential habitat suitability variations of Chilgoza pine under varying environmental scenarios by using 37 different environmental variables. The maximum entropy (MaxEnt) algorithm in MaxEnt software was used to forecast the potential habitat suitability under current and future (i.e., 2050s and 2070s) climate change scenarios (i.e., Shared Socio-economic Pathways (SSPs): 245 and 585). A total of 238 species occurrence records were collected from Afghanistan, Pakistan and India, and employed to build the predictive distribution model. The results showed that normalized difference vegetation index, mean temperature of coldest quarter, isothermality, precipitation of driest month and volumetric fraction of the coarse soil fragments (>2 mm) were the leading predictors of species presence prediction. High accuracy values (>0.9) of predicted distribution models were recorded, and remarkable shrinkage of potentially suitable habitat of Chilgoza pine was followed by Afghanistan, India and China. The estimated extent of occurrence (EOO) of the species was about 84,938 km2, and the area of occupancy (AOO) was about 888 km2, with 54 major sub-populations. This study concluded that, as the total predicted suitable habitat under current climate scenario (138,782 km2) is reasonably higher than the existing EOO, this might represent a case of continuous range contraction. Hence, the outcomes of this research can be used to build the future conservation and management plans accordingly for this economically valuable species in the region.

Half of the productive forest area in Sweden is owned by small-scale private forest owners. However, there is a lack of comprehensive information that would allow categorizing small-scale private forest owners according to their management strategy. In this study, we surveyed small-scale private forest owners in Sweden to determine the proportions who applied various management strategies. We analyzed the results using chi-square tests to identify the most relevant factors affecting the management strategy choices of individual forest owners. We found that “soft” factors, such as the importance of income from the forest, membership in a forest owners’ association, certification and an interest in and knowledge of forestry issues, had a stronger impact on the choice of management strategy than most “hard” factors related to the owner or the property, such as gender and distance between the owner’s residence and the property. However, property size was the most important factor and was associated with the importance of income derived from the forest and several other soft factors.

Droughts negatively impact forests by reducing growth and increasing defoliation leading to forest dieback as the climate becomes warmer and drier. However, the timing and severity of droughts determine how differently or intensively water shortage affects primary (shoot and leaf formation) and secondary growth (stem radial growth based on tree-ring widths). We compare the impact of two severe droughts (2005, 2012), showing different climatic characteristics on the growth responses of three Mediterranean holm oak stands in northeastern Spain. We also quantify climate trends and drought severity. Then, we use remote sensing data to infer how those droughts impacted forest productivity. Both droughts were characterized by warm and dry spring conditions leading to reduced budburst, low shoot production, asynchrony in primary growth and decreased productivity and scarce radial growth, particularly in 2005. However, defoliation peaked in 2012 when radial growth showed minimum values and early spring and late summer temperatures reached maximum values. We discuss how uncoupled and resilient are the responses of primary and secondary growth to drought. Finally, these findings are used to gain insight into the drought-related drivers of defoliation in Spanish holm oak forests.

A detailed understanding of species distribution is usually a prerequisite for the rehabilitation and utilization of species in an ecosystem. Paeonia veitchii (Paeoniaceae), which is an endemic species of China, is an ornamental and medicinal plant that features high economic and ecological values. With the decrease of its population in recent decades, it has become a locally endangered species. In present study, we modeled the potential distribution of P. veitchii under current and future conditions, and evaluated the importance of the factors that shape its distribution. The results revealed a highly and moderately suitable habitat for P. veitchii that encompassed ca. 605,114 km2. The central area lies in northwest Sichuan Province. Elevation, temperature seasonality, annual mean precipitation, and precipitation seasonality were identified as the most important factors shaping the distribution of P. veitchii. Under the scenario with a low concentration of greenhouse gas emissions (RCP 2.6), we predicted an overall expansion of the potential distribution by 2050, followed by a slight contraction in 2070. However, with the scenario featuring intense greenhouse gas emissions (RCP 8.5), the range of suitable habitat should increase with the increasing intensity of global warming. The information that was obtained in the present study can provide background information related to the long-term conservation of this species.

A solution to the growing problem of catastrophic wildfires in Greece will require a more holistic fuel management strategy that focuses more broadly on landscape fire behavior and risk in relation to suppression tactics and ignition prevention. Current fire protection planning is either non-existent or narrowly focused on reducing fuels in proximity to roads and communities where ignitions are most likely. A more effective strategy would expand the treatment footprint to landscape scales to reduce fire intensity and increase the likelihood of safe and efficient suppression activities. However, expanding fuels treatment programs on Greek landscapes that are highly fragmented in terms of land use and vegetation requires: (1) a better understanding of how diverse land cover types contribute to fire spread and intensity; and (2) case studies, both simulated and empirical, that demonstrate how landscape fuel management strategies can achieve desired outcomes in terms of fire behavior. In this study, we used Lesvos Island, Greece as a study area to characterize how different land cover types and land uses contribute to fire exposure and used wildfire simulation methods to understand how fire spreads among parcels of forests, developed areas, and other land cover types (shrublands, agricultural areas, and grasslands) as a way to identify fire source–sink relationships. We then simulated a spatially coordinated fuel management program that targeted the fire prone conifer forests that generally burn under the highest intensity. The treatment effects were measured in terms of post-treatment fire behavior and transmission. The results demonstrated an optimized method for fuel management planning that accounts for the connectivity of wildfire among different land types. The results also identified the scale of risk and the limitations of relying on small scattered fuel treatment units to manage long-term wildfire risk.

Urban green infrastructure plays an increasingly significant role in sustainable urban development planning as it provides important regulating and cultural ecosystem services. Monitoring of such dynamic and complex systems requires technological solutions which provide easy data collection, processing, and utilization at affordable costs. To meet these challenges a pilot study was conducted using a network of wireless, low cost, and multiparameter monitoring devices, which operate using Internet of Things (IoT) technology, to provide real-time monitoring of regulatory ecosystem services in the form of meaningful indicators for both human health and environmental policies. The pilot study was set in a green area situated in the center of Moscow, which is exposed to the heat island effect as well as high levels of anthropogenic pressure. Sixteen IoT devices were installed on individual trees to monitor their ecophysiological parameters from 1 July to 31 November 2019 with a time resolution of 1.5 h. These parameters were used as input variables to quantify indicators of ecosystem services related to climate, air quality, and water regulation. Our results showed that the average tree in the study area during the investigated period reduced extreme heat by 2 °C via shading, cooled the surrounding area by transferring 2167 ± 181 KWh of incoming solar energy into latent heat, transpired 137 ± 49 mm of water, sequestered 8.61 ± 1.25 kg of atmospheric carbon, and removed 5.3 ± 0.8 kg of particulate matter (PM10). The values of the monitored processes varied spatially and temporally when considering different tree species (up to five to ten times), local environmental conditions, and seasonal weather. Thus, it is important to use real-time monitoring data to deepen understandings of the processes of urban forests. There is a new opportunity of applying IoT technology not only to measure trees functionality through fluxes of water and carbon, but also to establish a smart urban green infrastructure operational system for management.