Forest Types Research Articles

The Short-Term Responses of Forest Soil Invertebrate Communities to Typhoon Disturbances

Knowledge regarding the response of soil invertebrate communities to typhoon disturbance is limited, although it is known that soil invertebrates are sensitive to forest disturbances and that tropical cyclones (typhoons/hurricanes) are the most destructive natural disasters affecting the structure and function of forest ecosystems. To fill this knowledge gap, soil invertebrates in both litter and topsoil layers were investigated in four representative subtropical coastal forests of eastern China one week before the first typhoon (Hinnamnor) (T1), one day after the first typhoon (Hinnamnor) (T2), one day after the second typhoon (Muifa) (T3), and one week after the second typhoon (Muifa) (T4) in September 2022. Typhoon disturbances decreased the density and taxa abundance of soil invertebrate communities in litter layer, but the first typhoon disturbance increased these values in the topsoil layer. One week after the second typhoon disturbance, soil invertebrate communities in the litter layer showed a gradual recovery trend. Meanwhile, the soil invertebrate communities in the litter layer were more sensitive to typhoon disturbances than those in the topsoil layer. Furthermore, the responses of the soil invertebrate communities to the typhoon disturbances varied greatly with the forest types. The invertebrate densities in the litter layer decreased by 62.1%, 63.53%, 47.01%, and 46.92% in Chinese fir, second broad-leaved, mixed, and bamboo forests, respectively. Particularly, these two non-catastrophic typhoons significantly altered the functional group composition of detrital food webs in the short term, and the proportion of phytophages in detrital food webs in the litter layer increased after the typhoon disturbances. In conclusion, the effects of typhoon disturbances on soil invertebrate communities vary greatly with forest type and soil layer, and soil invertebrate communities can gradually recover after typhoon disturbances. The legacy effects of typhoon disturbances on the functional group composition of detrital food webs may influence carbon and nutrient cycling in forest ecosystems.

An optimal ensemble of the CoLM for simulating the carbon and water fluxes over typical forests in China

Stomatal conductance (gs) and compensatory water uptake (CWU) are crucial processes in land surface models, as they directly influence the exchange of carbon and water fluxes between terrestrial ecosystems and the atmosphere. In this study, we integrated a new stomatal scheme derived from optimal stomatal theory (Medlyn's gs model), and an empirical CWU scheme into the Common Land Model (CoLM). Assessing the impacts on modeling gross primary productivity (GPP) and latent flux (LE) through observations obtained from eddy covariance (EC) measurements at three forest sites in China. Our results show that replacing the Ball-Berry's gs model (termed BB) with Medlyn's gs model (termed MED) did not bring about significant changes (had neutral impacts) in the performance of CoLM simulations at three forest sites. Considering the climate factors of annual mean precipitation to optimize key fitting parameters in gs exhibited improvement in model simulations. The average coefficient of determination (R2) achieved to 0.65 for GPP and LE at three sites, and the normalized root mean squared error (NRMSE) decreased from 0.83 to 0.77 at those sites. Besides, incorporating CWU into the model improved its performance. The R2 increased to 0.84 and RMSE decreased to 4.84 μmol m−2 s−1 for GPP, and the R2 increased to 0.62 and RMSE decreased to 55.64 W m−2 for LE. Therefore, modifying the model process of both contributed more to enhancing the model simulations than relying solely on one of these functions. Our study highlights that the response of plant functional types (PFTs) to water stress can be effectively represented in gs models when coupled with biochemical capacity to quantify carbon and water fluxes in forest ecosystems or other ecosystems.

Temporal and spatial patterns of fire regime disruption in conifer forests of western North America

ABSTRACT Temporal and spatial patterns of fire regime disruption were reconstructed in conifer forests of western North America from information on pre-disruption and disrupted mean fire intervals (MFIs) of 498 dendrochronology-based fire chronologies. We identified the conifer forest types most affected by MFI shift and the influence of land category designation on MFI change. We also mapped the years of the MFI shift, the last fire recorded, and disrupted/pre-disruption MFI ratios. Fire cessation and longer MFIs predominated in most fire chronologies and conifer forest types. MFI was significantly higher in most conifer forest types, with most differences in dry conifer forests. MFI shift occurred mainly before the designation of protected, federal, social-property, and private areas. MFI shift began in 1829 in the United States of America Southwest, a region subjected to prolonged fire exclusion and with the highest disrupted/pre-disruption MFI ratios. Fire regime disruption moved gradually into the Pacific Northwest and the Sierra Nevada until reaching the northern conifer forests of Canada and Alaska. In contrast, one-third of fire chronologies in Mexican conifer forests retained pre-disruption MFIs. Our findings allowed us to identify areas with MFIs outside of their natural variability, with prolonged fire exclusion, or with intact fire regimes.

Long-term trends and response of wet ammonia deposition to changes in anthropogenic emissions in the Pearl River delta of China

The Pearl River Delta (PRD) region has been identified as a significant hotspot of wet ammonium deposition. However, the absence of long-term monitoring data in the area hinders the comprehension of the historical trends and changes in wet NH4+-N deposition in response to emissions, which interferes with the ability to make effective decisions. This study has analyzed the long-term trends of wet NH4+-N deposition flux and has quantified the effect of anthropogenic emissions and meteorological factors at a typical urban site and a typical forest site in the PRD region from 2009 to 2020. It revealed a significant decreasing trend in wet NH4+-N flux in both the typical urban and forest areas of the PRD region, at -6.2%/year (p < 0.001) and -3.3%/year (p < 0.001), respectively. Anthropogenic emissions are thought to have contributed 47–57% of the wet NH4+-N deposition trend over the past 12 years compared to meteorological factors. Meteorological conditions dominated the inter-annual fluctuations in wet NH4+-N deposition with an absolute contribution of 46%–52%, while anthropogenic emissions change alone explained 10%–31%. NH3 emissions have the greatest impact on the urban area among anthropogenic emission factors, while SO2 emissions have the greatest impact on the forest area. Additionally, precipitation was identified as the primary meteorological driver for both sites. Our findings also imply that the benefits of NH3 emissions reductions might not immediately emerge due to interference from weather-related factors.

Retention forestry amplifies microclimate buffering in boreal forests

Retention forestry is increasingly adopted as an alternative to clearcutting practices and involves retaining structural and compositional complexity (e.g., living and dead trees) from preharvest to postharvest. Past studies have examined the role of retention forestry in supporting various ecosystem functions and biodiversity, whilst its microclimate buffering capacity has been largely neglected. We investigated the microclimates and the underlying mechanisms of retention forests relative to clearcuts and old forests in a boreal forest landscape in central Sweden. We found that both air temperature and vapour pressure deficit (VPD) differed significantly between the forest types. Old forests consistently exhibited the most buffered forest microclimates, followed by retention forests, while clearcuts displayed the lowest. Basal area and canopy cover were identified as the key determinants influencing air temperature and VPD across the forest types. Retention practices can also impact a stand's microclimates. Specifically, maintaining diverse tree species had the potential to lower the stand's maximum temperature, given its positive association with canopy cover. Large volumes of lying deadwood were found to be negatively correlated with both basal area and canopy cover, likely contributing to increased maximum temperatures. Furthermore, standing deadwood directly lowered the maximum temperature within forest stands. Finally, edge effects were observed in the retention forests, with south-facing edges experiencing significantly higher maximum temperature and VPD compared to north-facing edges and forest interiors. These south-facing edge effects were positively associated with the difference in lying deadwood volumes between forest edges and interiors. Our findings support the positive influence of retention practices on a stand's microclimate buffering, achieved through preserving diverse tree species, standing deadwood, and implementing measures to prevent severe wind-induced tree mortality, particularly in south-facing edges (e.g. creating south-facing buffer zones). Forest managers and policy makers can utilize these results to minimize the climate-change impacts on below-canopy biodiversity and functioning.

Restoring Subtropical Forests: Alleviating P Limitation and Introducing C Limitation Using Evergreen Broad-Leaved Tree Species

Determining which species to utilize for the artificial restoration of subtropical secondary forests has become a focal point in forestry and ecology. To compare the effects of the subtropical secondary forest artificial restoration model on soil microbial nutrient acquisition and limitation, we examined secondary forests (CKs), evergreen coniferous forests (GCPs), evergreen coniferous mixed broad-leaved forests (GCBMs), evergreen mixed broad-leaved forests (GBMs), and natural deciduous broad-leaved mixed forests (DBMs) as research subjects. Among them, GCPs, GCBMs, and GBMs were dominated by the species of the early, middle, and climax stages of subtropical forest succession, respectively. The activities and stoichiometry of β-1,4-glucosidase (BG), β-1,4-N-acetylglucosaminidase (NAG), leucine aminopeptidase (LAP), and acid phosphatase (ACP) in the topsoil were analyzed. The results showed that the forest type significantly affects the activities of BG and LAP rather than NAG or ACP. The BG activity in DBMs was the lowest, while the LAP activity in CKs was significantly higher than that in plantations. Furthermore, the nutrient limitation of microbes was quantitatively analyzed by using the vector analysis of enzyme stoichiometry. The soil microbes in the study area were co-limited by C and P, and the nutrient limitation was in the order of C &gt; P &gt; N. Among the forests, the enzyme stoichiometric ratios in GCPs and DBMs were closest to 1:1:1. From CKs to GBMs, the microbial C limitation was increased, while the P limitation was decreased. The C limitation in DBMs was slightly lower than that in CKs. Overall, the P limitation in evergreen plantations was less than that in CKs. The soil bulk density, C/P, and N/P significantly influenced enzyme activities and stoichiometry. These results suggest that the artificial restoration of subtropical forests using evergreen species alleviated P limitation, while using deciduous broad-leaved species offered potential for alleviating microbial C limitation. Compared with evergreen broad-leaved species, employing pioneer and mid-successional or deciduous broad-leaved species can better achieve balanced microbial nutrient requirements.

Seed bank and aboveground vegetation of Atlantic Forest re‐growing on mining tailings in Mariana: Highlighting diversity patterns of functional groups

AbstractNatural regeneration after mining activities depends largely on the soil seed bank (SSB) and aboveground vegetation (AGV) richness and composition. We evaluated the species diversity pattern of the SSB and AGV on soil and technosol across second‐growth Atlantic Forests (SGFs) after mining tailings deposition in Mariana, southeastern Brazil. Two second‐growth Atlantic seasonal semideciduous forests of different stand ages were selected: a 3‐year‐old stand of SGF re‐growing on tailings (SGF tailings) and a 30‐year‐old stand of native reference forest not affected by tailings (SGF nontailings). Overall, the results showed significant differences in forest attributes (species richness and composition) in the SSB and AGV between the two forest patches evaluated (SGF tailings and SGF nontailings). Moreover, both nonzoochoric and zoochoric dispersed species of AGV showed significant differences between second‐growth forests, with higher variability of community‐weighted mean in SGF tailings. The result shows smaller differences in species richness between forest types for both SBB (ranging 85 and 90 species) and AGV (~55 species). Despite the time difference between the secondary forest and the absence of zoochoric species in the tailings seed bank, the AGV that are re‐growing on mining tailings presented a high proportion of zoochoric species. This pattern of species richness and community composition variability observed in the technosol seed bank, and AGV that are re‐growing after the deposition of mining tailings are important recovery indicators for plant communities affected.

Estimation of canopy height based on multi-source remote sensing data using forest structure aided sample selection

ABSTRACT Forest canopy height data are crucial for estimating forest carbon storage and assessing forest ecology. By utilizing satellite imagery, canopy height data obtained from airborne or spaceborne LiDAR have been expanded from footprint and plot levels to spatially continuous elevation mapping of forests. However, current research suggests that estimating forest canopy height without forest type data presents a challenge in how to effectively integrate multi-source LiDAR data and ensure the samples adequately represent various forest types for higher estimation accuracy. Therefore, this study proposes a forest canopy height estimation method that considers forest structure and integrates multi-source LiDAR data to overcome the challenge. First, a stratified sampling method based on forest structure (SSMFS) was proposed to select training samples and enhance their representativeness. Second, we combined GEDI and ATL08 data to create a multi-source spaceborne LiDAR dataset, enhancing geographic coverage and increasing canopy height samples. Third, the spaceborne LiDAR-based canopy height estimation model incorporates previously unconsidered canopy openness features and uses SSMFS to select training samples. Finally, we improved spaceborne LiDAR canopy height accuracy by creating a residual correction model that adjusts for differences between airborne scanner (ALS) and spaceborne LiDAR estimates. This study, conducted in Zhangwu County, achieved an accuracy of R2 = 0.71, MAE = 1.20 m, and RMSE = 1.71 m. These results show a 51.06% increase in R2, a 26.38% decrease in MAE, and a 24.00% decrease in RMSE compared to recent research. In summary, this study profoundly amplifies predictive accuracy, providing a clear advantage in the delineation of regional forest canopy maps.

Neighborhood competition modulates the link between crown structure and tree ring variability in monospecific and mixed forest stands

3D crown shape and tree ring development are autobiographies of the growth conditions. With advancements in terrestrial laser scanning, modeling growth from 3D crown structure offers insights into trees’ structural and functional responses in a non-destructive and repetitive way. However, how the trees in different growing conditions respond in 3D structure and manifest their responses into tree rings remains unexplored, which would help to better explain tree-level growth dynamics and forest management. To enhance this understanding, we tested a set of hypotheses: (HI) that 3D crown shape (CS) and tree ring (width) patterns (TRP) are correlated across different growing conditions or forest stands like monospecific, provenances trials, and mixed forest stands; (HII) that stand types influence the CS-TRP link; and (HⅢ) local neighborhood competition (LNC) modulates the CS-TRP link. (HⅣ) 3D crowns manifest local growth conditions; therefore, 3D crown structures can be used to predict tree ring growth. We assessed these hypotheses by employing terrestrial laser scanning-based 3D crown shape and dendrochronology-based tree ring width patterns from Norway spruce (Picea abies [L.] Karst.) trees growing in pure spruce (unthinned and thinned), provenances trial, and mixed-species trial (with European Beech, Fagus sylvatica [L.]) stands covering a large-scale competition gradient. We first show that 3D crown shape and TRP metrics differed significantly across forests (p<0.05) but were correlated (p<0.05). Neighborhood competition among the forest types influences the link between 3D crowns and tree rings. Pathway-based analyses revealed that neighborhood competition indirectly influences ring variability by modifying crown structure (p<0.05), suggesting local growth conditions are mostly manifested into crown shapes, leading to 3D crown shape-based low-error growth predictions (0.44 mm) across forest types. However, incorporating competition legacy information (competition over the last 30 years) in the model slightly improved the prediction performance (error reduced to 0.41 mm), further explaining that the crown likely loses growth information due to growing conditions (competition it faces and species with it is growing). This study reveals how trees in different growing conditions differed structurally and mechanized their responses in tree rings, providing crucial insights into tree-level growth dynamics and management.

The Constraints to Effective Implementing of Illegal Logging Prohibition Regulation in Nigeria

Since the adoption of the Non-Legally Binding Authoritative Statement of Principles for Global Consensus on the Management, Conservation and Sustainable Development of all types of Forest at the 1992 Earth Summit in Rio de Janeiro, the issue of combating deforestation remains one of the topical issues relating to climate change discussions globally. To combat deforestation, countries go beyond international conventions to institutionalize domestic frameworks to regulate illegal timber logging. However, the implementation of regulatory policies has been ineffective in countries like Nigeria. Situated within this problem, this study identified some domestic constraints affecting the effectiveness of timber logging regulation in Nigeria. To this end, data was collected from respondents using structured questionnaires. The data were analysed using the Pearson Product Moment Correlation Coefficient (PPMC) at a 0.05 level of significance. Constraints identified are corruption, insufficient legal framework, lack of coordination in regulation enforcement, inadequate staff, and the state monopoly of forest ownership.

Sub-meter tree height mapping of California using aerial images and LiDAR-informed U-Net model

Tree canopy height is one of the most important indicators of forest biomass, productivity, and ecosystem structure, but it is challenging to measure accurately from the ground and from space. Here, we used a U-Net model adapted for regression to map the canopy height of all trees in the state of California with very high-resolution aerial imagery 0.6 m from the USDA-NAIP program. The U-Net model was trained using canopy height models computed from aerial LiDAR data as a reference, along with corresponding RGB-NIR NAIP images collected in 2020. We evaluated the performance of the deep-learning model using 42 independent 1 km2 areas across various forest types and landscape variations in California. Our predictions of tree heights exhibited a mean error of 2.9 m and showed relatively low systematic bias across the entire range of tree heights present in California. In 2020, trees taller than 5 m covered ∼ 19.3% of California. Our model successfully estimated canopy heights up to 50 m without saturation, outperforming existing canopy height products from global models. The approach we used allowed for the reconstruction of the three-dimensional structure of individual trees as observed from nadir-looking optical airborne imagery, suggesting a relatively robust estimation and mapping capability, even in the presence of image distortion. These findings demonstrate the potential of large-scale mapping and monitoring of tree height, as well as potential biomass estimation, using NAIP imagery.

Leaf nutrient traits of planted forests demonstrate a heightened sensitivity to environmental changes compared to natural forests.

Leaf nutrient content (nitrogen, phosphorus) and their stoichiometric ratio (N/P) as key functional traits can reflect plant survival strategies and predict ecosystem productivity responses to environmental changes. Previous research on leaf nutrient traits has primarily focused on the species level with limited spatial scale, making it challenging to quantify the variability and influencing factors of forest leaf nutrient traits on a macro scale. This study, based on field surveys and literature collected from 2005 to 2020 on 384 planted forests and 541 natural forests in China, investigates the differences in leaf nutrient traits between forest types (planted forests, natural forests) and their driving factors. Results show that leaf nutrient traits (leaf nitrogen content (LN), leaf phosphorus content (LP), and leaf N/P ratio) of planted forests are significantly higher than those of natural forests (P< 0.05). The impact of climatic and soil factors on the variability of leaf nutrient traits in planted forests is greater than that in natural forests. With increasing forest age, natural forests significantly increase in leaf nitrogen and phosphorus content, with a significant decrease in N/P ratio (P< 0.05). Climatic factors are key environmental factors dominating the spatial variability of leaf nutrient traits. They not only directly affect leaf nutrient traits of planted and natural forest communities but also indirectly through regulation of soil nutrients and stand factors, with their direct effects being more significant than their indirect effects.

Improving the Simulation Accuracy of the Net Ecosystem Productivity of Subtropical Forests in China: Sensitivity Analysis and Parameter Calibration Based on the BIOME-BGC Model

Subtropical forests have strong carbon sequestration potential; however, the spatiotemporal patterns of their carbon sink are unclear. The BIOME-BGC model is a powerful tool for forest carbon sink estimation while the numerous parameters, as well as the localization, limit their application. This study takes three typical subtropical forests (evergreen broadleaf forest, EBF; evergreen needleleaf forest, ENF; and bamboo forest, BF) in China as examples, assesses the sensitivity of 43 ecophysiological parameters in the BIOME-BGC model both by the Morris method and the extended Fourier amplitude sensitivity test (EFAST), and then evaluates the net ecosystem productivity (NEP) estimation accuracy based on the dataset of the fiveFi long-term carbon flux sites of those three typical forests from 2000 to 2015. The results showed that (1) both sensitivity analysis methods can effectively screen out important parameters affecting NEP simulation while the Morris method is more computationally efficient and the EFAST is better in the quantitative evaluation of sensitivity. (2) The highly sensitive parameters obtained using the two methods are basically the same; however, their importance varies across sites and vegetation types, e.g., the most sensitive parameters are k for the EBF and ENF and Ract25 for the BF, respectively. (3) The optimized parameters successfully improved the NEP simulation accuracy in subtropical forests, with average correlation coefficients increased by 25.19% and normalized root mean square error reduced by 21.74% compared with those simulated by original parameters. This study provides a theoretical basis for the optimization of process model parameters and important technical support for accurate NEP simulations of subtropical forest ecosystems.

Forest carbon stock-based bioeconomy: Mixed models improve accuracy of tree biomass estimates

Tree biomass and carbon stock continue to be the most important contributors to a forest-based bioeconomy. Accurate estimation of tree biomass and carbon stock therefore is crucial for planning a sustainable bioeconomy based on sustained forest bioresource production and harvest. Precise carbon accounting is also of fundamental importance for a green carbon market as well as for an improved model of quantitative global carbon cycle. However, estimating biomass and carbon at a large spatial scale without causing significant environmental disruption has been posing a methodological challenge necessitating to evolve a robust yet accurate estimation method. Although forest-specific generalized allometric models are the most widely used method to estimate forest tree biomass and carbon stock, these either under- or over-estimate the values, particularly in mixed-species forests. To address this challenge, we employed mixed equations that included species-specific models or available models for a sister species that provided a more conservative estimate of stand-level tree biomass and carbon compared to the generalized equations. We gathered primary data on tree girth and height at the stand level from sub-tropical and temperate forests of Tawang river basin, Arunachal Pradesh, India for validation. We compiled 32 equations comprising 27 species-specific and 5 forest-specific generalized models from a global dataset of allometric models. The outputs from the mixed models were comparable with the results of the harvest studies conducted by other researchers in similar forest types validating the efficacy of mixed models at a landscape scale.

Spatial Distribution of Soil Organic Carbon in the Forests of Nepal

Soil organic carbon (SOC) is the major constituent of the soil organic matter. SOC stocks are determined by several factors such as altitude, slope, aspect, canopy cover, and vegetation type. Using the Third National Forest Inventory (2010–2014) data of Nepal, we assessed SOC status in forests at a national scale for the better understanding of the SOC distribution within Nepal. In this study, we estimated SOC against different factors and tested the spatial distribution of SOC using analysis of variance (ANOVA). The results showed that the forests located at a higher altitude have higher SOC accumulation. In particular, broadleaved forests exhibit a higher amount of carbon stock compared to other forest types. Moreover, forests with a larger canopy cover, located on a higher slope, and with a cooler aspect are associated with a higher accumulation of SOC. The SOC stock in the forest varies according to altitude, slope, aspect, canopy cover, and forest type, which might be attributed to the change in the microclimate of the area. The significant increase in SOC amount with the increase in slope, altitude, and crown cover helps to understand the extent of SOC distribution in forests. Broadleaved forests with a larger canopy cover in the higher altitude region have a higher SOC retention potential, which is likely to contribute to mitigating the impacts of climate change by sinking more carbon into the soil.

Mixed plantation forest litter improves microbial nitrogen transformation by increasing nitrogen metabolism related genes and key bacterial taxa in northern China

AbstractNitrogen (N) metabolism is a key metabolic pathway of nutrient cycling in forest ecosystems. However, the mechanisms by which mixed plantation forest litter improves microbial N transformation are poorly understood. Thus, we investigated the N characteristics, N metabolism‐related genes, and key microbial modules of litter and soil in three types of forests: coniferous (CP forest), broadleaf (BP forest), and mixed forests (MCBP forest). Results indicated that the total N (TN), total hydrolysable organic N (THON), and percentage values of NH4+‐N/TN and NO3−‐N/TN in BP forest and MCBP forest litter were higher than those of CP forest litter, which was attributed to the increase in abundance of N fixation genes and dissimilatory nitrate reduction genes. The MCBP forest increased the bacterial number and diversity, and the abundance of key bacterial taxa. Bacterial key modules 1 and 2 were identified, consisting of Acidobacteria, Actinobacteria, Chloroflexi, Nitrospirae, Proteobacteria, and Gemmatimonadetes, while archaeal module 5 was also a key module, comprising Thaumarchaeota and Euryarchaeota. Nutrients were the limiting factor of key microbial modules in the decomposition of litter, further influencing N metabolism‐related genes and enzymes. Therefore, mixed plantation forests increased microbial N fixation and transformation during litter decomposition in northern China.

Spatial and temporal monitoring of wildfires in Golestan province using remote sensing data

Wildfires are one of the most significant factors of ecosystem change. Knowing the wildfire regime (frequency, intensity, and distribution pattern) is essential in wildfire management. This research aims to analyze the spatiotemporal pattern of wildfires in Golestan in 2001-2021 using MODIS data, burned area product (MCD64A1). For this purpose, the annual and monthly frequency, as well as the trend of wildfires based on types of forest, pasture, and crop cover, were statistically analyzed. The local Moran pattern analysis method and kernel density function were used to analyze the spatial dynamics of wildfire. The results showed that 18,462 wildfires occurred in Golestan, the highest of which was in 2010, with 2,517 wildfires (13.8%). The lowest number of wildfires, with only 57 events (0.5%), was in 2001. Based on the local Moran model results and the kernel density function, the wildfires' extent and intensity were greater in the plains and foothills to the south and southeast of Golestan. The lowest extent and intensity of the wildfire corresponded to the eastern parts of the province. The frequency of wildfires was higher in the hot period of the year (spring and summer). However, the period of occurrence of wildfire and the peak of wildfire changes in different uses. The wildfire zones in June were wider and more intense than in other months. The frequency and spatial extent of wildfires in agricultural lands from May to July, pasture lands in July, August, and September, and forest lands in November and December were more than in other months. Weather conditions play a significant role in the occurrence of wildfire in the forest lands of Golestan. The results of this research help understand wildfire risk areas and provide a scientific basis for predicting and controlling wildfires and reducing carbon emissions related to them.

The influence of stand composition and season on canopy structure and understory light environment in different subtropical montane Pinus massoniana forests.

Canopy structure and understory light have important effects on forest productivity and the growth and distribution of the understory. However, the effects of stand composition and season on canopy structure and understory light environment (ULE) in the subtropical mountain Pinus massoniana forest system are poorly understood. In this study, the natural secondary P. massoniana-Castanopsis eyrei mixed forest (MF) and P. massoniana plantation forest (PF) were investigated. The study utilized Gap Light Analyzer 2.0 software to process photographs, extracting two key canopy parameters, canopy openness (CO) and leaf area index (LAI). Additionally, data on the transmitted direct (Tdir), diffuse (Tdif), and total (Ttot) radiation in the light environment were obtained. Seasonal variations in canopy structure, the ULE, and spatial heterogeneity were analyzed in the two P. massoniana forest stands. The results showed highly significant (P < 0.01) differences in canopy structure and ULE indices among different P. massoniana forest types and seasons. CO and ULE indices (Tdir, Tdif, and Ttot) were significantly lower in the MF than in the PF, while LAI was notably higher in the MF than in the PF. CO was lower in summer than in winter, and both LAI and ULE indices were markedly higher in summer than in winter. In addition, canopy structure and ULE indices varied significantly among different types of P. massoniana stands. The LAI heterogeneity was lower in the MF than in the PF, and Tdir heterogeneity was higher in summer than in winter. Meanwhile, canopy structure and ULE indices were predominantly influenced by structural factors, with spatial correlations at the 10 m scale. Our results revealed that forest type and season were important factors affecting canopy structure, ULE characteristics, and heterogeneity of P. massoniana forests in subtropical mountains.

Phytocenosis With the Participation of Species of the Gentiana L. Genus on the Territory of Azerbaijan

Gentian species are found in different types of vegetation in different regions of Azerbaijan. They are found mainly in grass, forest, rocky, shrub and forest types of vegetation. These species are widespread in natural phytocenosis and play an important role in the formation of the biomass of phytocenosis. The main types of phytocenosis with the participation of gentian on the territory of Azerbaijan are described. A cenotic characteristic is given.

Wildfires affect mesocarnivores habitat use and mammalian predator-prey relationships in a Mediterranean ecosystem

Effects of fires on carnivores are still poorly understood, particularly in the fire-prone Mediterranean basin. For instance, whether the effects are mainly mediated by prey abundance (Prey Abundance Hypothesis, PAH), prey catchability (Prey Catchability Hypothesis, PCH) or habitat suitability is unclear. Our objective was to investigate the role of fire, mammalian prey abundance, habitat suitability and their interactions in shaping the use of space and time of two carnivores, i.e., the red fox Vulpes vulpes and the stone marten Martes foina. The study area was Monte Pisano (Italy), where 12 km2 of surface burned in 2018. In early summer 2021 a stratified random sampling design was implemented, with fire and forest type as main strata. Fifty sites were selected, and two infrared cameras were placed at each site. Camera data were used to develop single-species occupancy models for the two predators, whereas time overlap between theme and their prey was evaluated through the Mardia-Watson-Wheeler test. Fox occupancy decreased with increasing herbaceous cover, but only when “mouse and voles” abundance was medium to high, regardless of habitat type. Fox also had significant differences in temporal activity between burnt and unburnt areas, not coupled by a similar pattern for its prey. In contrast, stone marten occupancy mainly depended on canopy cover. The fox could have adapted its hunting strategy to features of the environment and prey abundance, somehow supporting both PCH and PAH. In time, this species could optimize its activity in burnt and unburnt areas according to the brightness of the night. Differences in activity in “mice and voles” were interpreted as anti-predatory responses to the fox. Lastly, the stone marten did not pursue its prey in open areas. In conclusion, carnivores’ habitat use and mammalian predator-prey relationships were overall influenced by fire and post-fire successions.