Forest In Northeast China Research Articles

A comparison of five models in predicting surface dead fine fuel moisture content of typical forests in Northeast China

IntroductionThe spread and development of wildfires are deeply affected by the fine fuel moisture content (FFMC), which is a key factor in fire risk assessment. At present, there are many new prediction methods based on machine learning, but few people pay attention to their comparison with traditional models, which leads to some limitations in the application of machine learning in predicting FFMC.MethodsTherefore, we made long-term field observations of surface dead FFMC by half-hour time steps of four typical forests in Northeast China, analyzed the dynamic change in FFMC and its driving factors. Five different prediction models were built, and their performances were compared.ResultsBy and large, our results showed that the semi-physical models (Nelson method, MAE from 0.566 to 1.332; Simard method, MAE from 0.457 to 1.250) perform best, the machine learning models (Random Forest model, MAE from 1.666 to 1.933; generalized additive model, MAE from 2.534 to 4.485) perform slightly worse, and the Linear regression model (MAE from 2.798 to 5.048) performs worst.DiscussionThe Simard method, Nelson method and Random Forest model showed great performance, their MAE and RMSE are almost all less than 2%. In addition, it also suggested that machine learning models can also accurately predict FFMC, and they have great potential because it can introduce new variables and data in future to continuously develop. This study provides a basis for the selection and development of FFMC prediction in the future.

Multiple spectral comparison of dissolved organic matter in the drainage basin of a reservoir in Northeast China: Implication for the interaction among organic matter, iron, and phosphorus

Dissolved organic matter (DOM) plays a major role in ecological systems, affecting the fate and transportation of iron (Fe) and phosphorus (P). To better understand the geochemical cycling of these components, soil and sediment samples were collected around a reservoir downstream of a typical temperate forest in Northeast China. The DOM fractions from these soils, river, and reservoir sediments were extracted and then characterized by spectroscopic techniques. Comparative characterization data showed that the DOM pool of the Xishan Reservoir was partly autochthonous and derived from runoff and deposition of material in terrestrial ecosystems upstream. The upper reaches of the reservoir had significantly lower total Fe (TFe) content in the DOM extracts than those found in the reservoir (p < 0.05). Within the DOM, TFe was correlated with the amino acid tryptophan (p < 0.01). There was also a strong positive correlation between total P (TP) concentrations in DOM and tyrosine (p < 0.01). Organic P (Po) comprised most of the DOM TP, and was related to dissolved organic carbon (DOC) content and the amino acid tyrosine (p < 0.01). The interaction among DOM, Fe, and P appears to be due to complexation with tryptophan (Fe) and tyrosine (P). This suggests that the formation of Fe-DOM-P would be produced more readily than DOM-Fe-P complexes under optimal conditions. The interaction among DOM, Fe, and P can promote the coordinated migration, transformation, and ultimate fate of components that are complex with DOM from riverine and reservoir ecosystems, ultimately leading to accumulation within a reservoir and transport to downstream regions when reservoir dams are released. Reservoir dams can effectively intercept DOM and minerals prevent its flow downstream; however, it is important to understand the co-cycling of DOM, Fe and P within reservoirs, downstream rivers, and ultimately oceans. The involvement of amino acid components of DOM, tyrosine and tryptophan, in DOM complexation is an issue that requires further study.

Seasonal variation in the soil fungal community structure of Larix gmelinii forests in Northeast China.

Soil fungi play an indispensable role in forest ecosystems by participating in energy flow, material circulation, and assisting plant growth and development. Larix gmelinii is the dominant tree species in the greater Khingan Mountains, which is the only cold temperate coniferous forest in China. Understanding the variations in underground fungi will help us master the situation of L. gmelinii above ground. We collected soil samples from three seasons and analyzed the differences in soil fungal community structure using high-throughput sequencing technology to study the seasonal changes in soil fungal community structure in L. gmelinii forests. We found that the Shannon and Chao1 diversity in autumn was significantly lower than in spring and summer. The community composition and functional guild varied significantly between seasons. Furthermore, we showed that ectomycorrhizal fungi dominated the functional guilds. The relative abundance of ectomycorrhizal fungi increased dramatically from summer to autumn and was significantly negatively correlated with temperature and precipitation. Temperature and precipitation positively affect the alpha diversity of fungi significantly. In addition, pH was negatively correlated with the Chao1 diversity. Temperature and precipitation significantly affected several dominant genera and functional guilds. Among the soil physicochemical properties, several dominant genera were affected by pH, and the remaining individual genera and functional guilds were significantly correlated with total nitrogen, available phosphorus, soil organic carbon, or cation exchange capacity. For the composition of total fungal community, temperature and precipitation, as well as soil physicochemical properties except AP, significantly drove the variation in community composition.

Differentiating effects of salvage logging and recovery patterns on post-fire boreal forests in Northeast China using a modified forest disturbance index

ABSTRACT Forests are resilient to a range of disturbances, but combinations of severe natural and anthropogenic disturbances (e.g. wildfire and logging) may inhibit forest recovery and lead to forest degradation. Recent studies have explored long-term forest-disturbance detection and forest-recovery dynamics by using free and open-access remote-sensing images. However, mapping consecutive multiple disturbance agents is challenging using existing automated change-detection algorithms because the reduced canopy reflectance and the smoothing of consecutive disturbance signals mean that the initial disturbance cannot be spectrally separated from the second disturbance. Furthermore, uncertainty remains about post-disturbance vegetation dynamics and the effects of forest recovery under the interaction of burn severity, biological-legacy management, and active forest restoration (i.e. artificial regeneration and assisted natural regeneration). This contributes to biases in long-term forest-recovery monitoring, which are not conducive to the guidance of post-fire vegetation recovery. Here, we propose a modified disturbance index to separate the spectral characteristics of fire and forest logging using normalized tasseled-cap components (brightness and wetness) and detect the spatiotemporal distribution of post-fire logging by means of an index threshold and image differencing. On this basis, the recovery patterns of the post-fire forest are differentiated by considering the cumulative effect of fire, post-fire logging, and recovery approaches. The method is tested in the burn areas of the 5.6 Fire in the Greater Hinggan Mountain area (the largest forest fire in recorded history in China), giving an overall accuracy of 85% in post-fire forest logging mapping. Our results confirm that biological legacies (i.e. trees, logs, and snags) were removed across many areas in the fire, with activities peaking in the second year after the fire and located chiefly in areas of moderate and high burn severity. By identifying post-fire logging, the fluctuation and high disturbance index of the conventional temporal trajectory in the early stage of forest recovery are explained. The large-scale salvage logging slowed the recovery of the post-fire forest ecosystem and influenced the recovery process through the interaction of burn severity and active forest restoration. In areas of high burn severity, assisted natural regeneration (i.e. natural regeneration with artificial aids such as clearing the snags, weeding, digging pits, and supplemental planting) preserved biological legacies and achieved a higher proportion of forest recovery, second only to non-logged areas where natural regeneration (i.e. forestry recovering naturally without any artificial intervention) occurred. By contrast, salvage logging followed by artificial regeneration (i.e. clear-cutting all dead or damaged trees followed by tree planting or artificial seeding) hindered vegetation recovery in the early stage, but it improved the recovery rate in years 10–20 and approached the recovery proportion of non-logged areas where natural regeneration occurred as the recovery progressed and habitat conditions improved. The proposed method is shown to offer important advantages in detecting post-fire salvage logging, and it provides improved guidance for forest managers in developing strategies for forest recovery.

Age-related patterns and climatic driving factors of drought-induced forest mortality in Northeast China

Given the significantly increasing frequency and intensity of droughts in Northeast China under climate change, it is necessary to understand drought-induced mortality in forest ecosystems. The magnitude of drought-induced forest mortality strongly depends on climate variability and forest age, which are both important driving factors of tree mortality. However, the age-related patterns and climatic driving factors of drought-induced forest mortality at large scales are poorly understood. This study identified the age-related pattern and the key climatic driving factors of drought-induced mortality for 17 dominant tree species in Northeast China using rain-use efficiency (RUE), standardized precipitation evapotranspiration index (SPEI), and tree-list information (species and diameter for every tree). Considering that climate variability and forest age are important factors of drought-induced mortality, species-specific analysis was conducted for describing age-dependent mortality patterns. The results showed that the mean annual rate of the drought-induced mortality of forests in Northeast China was 0.49%, with relatively high mortality rates in the Changbai Mountains and the eastern part of Liaoning Province. The sensitivity of age-dependent mortality patterns to climatic drivers of drought exhibited considerable variability. Resolving the contributions of precipitation deficits and heatwaves on the drought-induced mortality of trees, almost 91.60% of the forest region in Northeast China was found to be primarily affected by heatwaves (temperature anomalies), suggesting the important role of temperature extremes in forest mortality. The findings provide deeper insight into the mechanisms behind the species-specific formation of age-dependent patterns in Northeast China. This study provides a basis for the formulation of drought adaptation measures for forest species across successional stages and highlights the potential of remote sensing indices in identifying the patterns and climatic drivers of large-scale drought-induced forest mortality.

Pipe Model Can Accurately Estimate Crown Biomass of Larch (Larix olgensis) Plantation Forest in Northeast China

The pipe model theory has been applied to estimate allometry of trees in many regions; however, its reliability and generality need more verification for estimating crown biomass in China. In the present study, the crown biomass of Larix olgensis plantations in four sites in northeast China was estimated using the pipe model, and the correlation efficiency index of larch crown biomass for pipe model estimation was 0.953. The crown biomass of larch plantations could be accurately estimated by the tree height, crown base height, and stem area at breast height. Meanwhile, the effects of site, stand density, and age on the accuracy of crown biomass estimated by the pipe model were detected. The covariance analysis showed that the effect of age on crown biomass was 0.024, indicating that age had a significant effect on the estimation accuracy in this model, while site and stand density had no significant effects (p = 0.180 and p = 0.169). Our study showed that the crown biomass of L. olgensis plantations in northeast China could be accurately estimated using the pipe model, and we recommend considering the age effect in practical applications.

Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data

ABSTRACT Recent growth in unmanned aerial vehicle (UAV) technology have promoted the detailed mapping of individual tree species. However, the in-depth mining and comprehending of the significance of features derived from high-resolution UAV data for tree species discrimination remains a difficult task. In this study, a state-of-the-art approach combining UAV-borne light detection and ranging (LiDAR) and hyperspectral was used to classify 11 common tree species in a typical natural secondary forest in Northeast China. First, comprehensive relevant structural and spectral features were extracted. Then, the most valuable feature sets were selected by using a hybrid approach combining correlation-based feature selection with the optimized recursive feature elimination algorithm. The random forest algorithm was used to assess feature importance and perform the classification. Finally, the robustness of features derived from point clouds with different structures and hyperspectral images with different spatial resolutions was tested. Our results showed that the best classification accuracy was obtained by combining LiDAR and hyperspectral data (75.7%) compared to that based on LiDAR (60.0%) and hyperspectral (64.8%) data alone. The mean intensity of single returns and the visible atmospherically resistant index for red-edge band were the most influential LiDAR and hyperspectral derived features, respectively. The selected features were robust in point clouds with a density not lower than 5% (~5 pts/m2) and a resolution not lower than 0.3 m in hyperspectral data. Although canopy surface features were slightly different from original LiDAR features, canopy surface information was also important for tree species classification. This study proved the capabilities of UAV-borne LiDAR and hyperspectral data in natural secondary forest tree species discrimination and the potential for this approach to be transferable to other study areas.

Spatial distribution and influencing factors of humus layer thickness of forest land in permafrost region of Northeast China

Humus has significant impacts on soil water dynamics, nutrient storage and plant growth. Studies have demonstrated that the humus layer is related to climate, soil properties, topography and other environmental factors. However, the thickness of the humus layer (HLT) and its spatial distributions are less investigated. Especially in boreal mountain forests underlain with permafrost, the environmental influences on HLT remain unclear. In a high-latitude watershed of boreal mountain forest in Northeast China, this study explores the effects of the environmental factors on HLT, and its relationships with permafrost types. The HLT distribution across the watershed is extracted using the geographically weighted regression kriging (GWRK) model. The elevation, slope, aspect, mean annual ground surface temperature and mean annual soil water content are determined to be statistically significant influencers factors of HLT. The elevation is the most important variable for HLT in this cold land, with an indirect effect on HLT through impacting ground surface temperature and soil water content. Topography casts more significant impact than ground surface temperature and soil water content. HLT ranges from 1.1 to 26.7 cm across three permafrost classes in the study area, decreasing with the discontinuity of permafrost types (continuous permafrost > sporadic permafrost > isolated patches). The findings suggest that the humus development is closely related to the permafrost type in northern high latitudes, and the permafrost degradation can lead to humus layer thinning under climate warming.

Ring- and diffuse-porous tree species from a cold temperate forest diverge in stem hydraulic traits, leaf photosynthetic traits, growth rate and altitudinal distribution.

In cold and humid temperate forests, low temperature, late frost and frequent freeze-thaw cycles are the main factors limiting tree growth and survival. Ring- and diffuse-porous tree species differing in xylem anatomy coexist in these forests, but their divergent adaptations to these factors have been poorly explored. To fill this knowledge gap, we compared four ring-porous and four diffuse-porous tree species from the same temperate forest in Northeast China by quantifying their leaf and stem functional traits, their stem growth rates using tree ring analysis and their resistance to cold represented by upper altitude species distribution borders from survey data. We found that the ring-porous trees were characterized by traits related to more rapid water transport, carbon gain and stem growth rates than those of the diffuse-porous species. Compared with the diffuse-porous species, the ring-porous species had a significantly higher shoot hydraulic conductance (Ks-shoot, 0.52 vs 1.03kgm-1s-1MPa-1), leaf photosynthetic rate (An, 11.28 vs 15.83μmolm-2s-1), relative basal area increment (BAIr, 2.28 vs 0.72cmyear-1) and stem biomass increment (M, 0.34 vs 0.09kgyear-1m-1). However, the observed upper elevational distribution limit of the diffuse-porous species was higher than that of the ring-porous species and was associated with higher values of conservative traits, such as longer leaf life span (R2=0.52). Correspondingly, BAIr and M showed significant positive correlations with acquisitive traits such as Ks-shoot (R2=0.77) and leaf photosynthetic rate (R2=0.73) across the eight species, with the ring-porous species occurring at the fast-acquisitive side of the spectrum and the diffuse-porous species located on the opposite side. The observed contrasts in functional traits between the two species groups improved our understanding of their differences in terms of growth strategies and adaptive capabilities in the cold, humid temperate forests.

Periodic harvests, rather than passive conservation, increase the carbon balance of boreal forests much more in Northeast China

Proper forest management can significantly contribute to global or regional carbon neutrality goals; however, the effects of different harvesting strategies on the carbon balances of forest sectors are still not clear. The motivation of this study was to develop a simulation–optimization system that can concurrently maximize the total economic benefits from timber production, biofuel production, and carbon balancing under four alternative harvesting scenarios. The current strict protection strategy (NoCutting) in this region was set as the reference scenario, and the NoConstraints and EvenFlow scenarios were generated based on whether they included restrictions on the flow of harvest volume over time. A final scenario (PreDefine) was inspired by the management policy that was implemented in this region prior to the 2010s. The scenarios were applied to a 123,400 ha boreal forest in Northeast China over a 100 year horizon. All relevant carbon pools within the forestry sector, as well as the avoided emissions related to the substitution effects of using wood products and biofuels, were considered. The results indicated that increasing harvesting intensities significantly improved the carbon balances (1.6 to 5.1 times greater), carbon stock (1% to 7.1% greater) and profitability (1.33 to 4.95 times greater), during which scenario EvenFlow was the first-rank harvest scenario. Hereinto, the carbon balances of the forest under EvenFlow were increased by 0.57 ton ha−1 yr−1 in total, during which the net atmospheric benefits from forest ecosystems, wood productions and substitutions were approximately 0.05, 0.24, and 0.38 ton ha−1 yr−1, respectively, while approximately 0.09 and 0.01 ton ha−1 yr−1 were lost by using the bio and fossil fuels, respectively, during the planning period when compared with NoCutting. The sensitivity analysis revealed that both carbon prices and substitution rates have positive effects on the total carbon balances, while significant negative effects were observed for discount rates. Overall, our results highlighted that periodic harvests rather than passive conservation should be a priority for the sustainable management of boreal forests in Northeast China.

Effects of simulated warming on seasonal dynamics of herbaceous diversity in temperate secondary forests in Northeast China

Effects of simulated warming on seasonal dynamics of herbaceous diversity in temperate secondary forests in Northeast China

Effect of tree species and functional diversity on ecosystem multifunctionality in temperate forests of northeast China

Effect of tree species and functional diversity on ecosystem multifunctionality in temperate forests of northeast China

Comparison of leaf cost-benefit relationship for five pinnate compound-leaf tree species in temperate forests of northeast China

Comparison of leaf cost-benefit relationship for five pinnate compound-leaf tree species in temperate forests of northeast China

Effects of aspect on phenology of Larix gmelinii forest in Northeast China

The response of vegetation phenology to global climate change is one of the main forms in terrestrial ecosystem change, the study of vegetation phenology is an important complement to the understanding of how global climate change affects ecosystems in multiple dimensions. We selected the distribution area of Larix gmelinii in The Greater Khingan Mountains as a case area by eliminating the heterogeneity of vegetation types, with the support of Google Earth Engine platform, we studied the effects of different aspects and land surface temperature (LST) on remote sensing phenology (RSP) that is defined as start of growing season (SOS), end of growing season (EOS) and length of growing season (LOS) respectively in the study area through Normalized Difference Vegetation Index (NDVI) changes. The results showed that SOS advanced in different aspects during the study period, and the advance amplitude of SOS on the east and west aspect was greater than that on the south and north. Except for the east aspect, EOS showed a slight postponed, and LOS was prolonged on all aspects. The latitude difference between 51° and 53° N had no significant effect on L. gmelinii in different aspects. LST had an obviously direct effect on the RSP of L. gmelinii in different aspects, and the effect of LST on SOS and LOS was significantly greater than that on EOS. The effect of LST on SOS and LOS was significant in April and spring. The main contributor to the increase of LOS was the advance of SOS, while the postponed of EOS has a relatively small contribution to LOS. Due to the redistribution of meteorological factor by aspect, the spatial and temporal heterogeneity of RSP tends to be complex, so determining the same aspect is one of the main ways to reduce the phenological heterogeneity in the study of vegetation RSP.

Changing Spring Phenology of Northeast China Forests during Rapid Warming and Short-Term Slowdown Periods

The vast forests of Northeast China are under great pressure from climate change. Understanding the effects of changing climate conditions on spring phenology is of great significance to assessing the stability of regional terrestrial ecosystems. Using Normalized Difference Vegetation Index data from 1982 to 2013, this paper investigated the changes in the start date of the vegetation growing season (SOS) of two main forest types in Northeast China, analyzing the changes in temporal and spatial patterns of forest spring phenology before and during the recent short-term warming slowdown, and exploring the effects of day and night temperatures and precipitation on the start of the growing season. The results showed that, during the rapid warming period (1982–1998), the SOS of deciduous needleleaf forests (DNF) was significantly advanced (−0.428 days/a, p &lt; 0.05), while the rate of advance of SOS of deciduous broadleaf forests (DBF) was nonsignificant (−0.313 days/a, p &gt; 0.10). However, during the short-term slowdown (1998–2013), the SOS of DBF was strongly delayed (0.491 days/a, p &lt; 0.10), while the change in SOS of DNF was not significant (0.169 days/a, p &gt; 0.10). The SOS was sensitive to spring maximum temperature for both forest types during the analysis period. Increases in winter precipitation influenced the SOS during the rapid warming period for DNF; this combined with the increase in the spring maximum temperature contributed to the advance in SOS. The decrease in the spring maximum temperature during the short-term slowdown, combined with a decrease in the previous summer maximum temperature, contributed to the rapid delay of SOS for DBF. DBF SOS was also more influenced by lagged effects of prior conditions, such as previous autumn to spring precipitation during the rapid warming period and previous summer maximum temperature during the short-term slowdown. In general, SOS was mainly determined by changes in daytime thermal conditions; DNF is more sensitive to temperature increases and DBF is more sensitive to decreases. Different regional climate conditions lead to differences in the distribution of DNF and DBF, as well as in the response of SOS to climate change during the rapid warming and short-term slowdown periods.

Change in Soil Nitrogen 9 Years After Wildfire in a Cold Temperate Coniferous Forest in Northeast China

Change in Soil Nitrogen 9 Years After Wildfire in a Cold Temperate Coniferous Forest in Northeast China

Comparison of the Application of Different Process-Based Models in the Study of Spatio-Temporal Patterns of Ecosystem Service Value

Quantitative assessments of ecosystem service value (ESV) are of great significance for rational allocation of environmental resources and making regional ecological protection decisions. The method of equivalence factor per unit area is widely used for this purpose because of its simple algorithm. However, ESV is also affected by biotic and environmental factors (e.g., net ecosystem productivity (NEP) or precipitation), which are difficult to obtain at the regional scale, leading to uncertainty in ESV estimations. In this study, according to the equivalent factor modified by precipitation and NEP from four state-of-the-art process-based productivity models, i.e., CLM4.0, LPJDGVM, LPJGUESS and ORCHIDEE, we explored the temporal and spatial patterns of ESV of 15 administrative regions in northern China. The results show that the simulation accuracy of different models varied among four representative ecosystem types, i.e., typical steppe in northern China, alpine steppe in northwest China, farmland ecosystem in central China, and forest in northeast China, implying that model-based ESV estimates are ecosystem-specific. The ESV tends to decline from northeast to southwest in northern China. Regions with dense vegetation usually had high ESV due to better hydrological and thermal conditions. Low vegetation coverage areas, such as Qinghai and Xinjiang, had higher ESV because of their large geographical areas. The central and eastern developed regions without abundant natural resources had lower ESV due to their lower NEP. For different categories of ecosystem services, the regulation services (mainly water flow regulation services and climate regulation services) contributed the most to ESV. For the temporal dynamics, the total ESV of the 15 provinces, autonomous regions and municipalities showed an insignificant downward trend over the years. The regions with increasing trends of ESV were distributed in northwestern China, while pixels with decreasing trends of ESV were concentrated in northeastern China. Land use cover change may be the most important factor controlling the temporal dynamics of ESV. Our results can provide support for the enaction of reasonable strategies for ecological protection and economic development in northern China.

Seasonal Influence of Biodiversity on Soil Respiration in a Temperate Forest

Soil respiration in forests contributes to significant carbon dioxide emissions from terrestrial ecosystems but it varies both spatially and seasonally. Both abiotic and biotic factors influence soil respiration but their relative contribution to spatial and seasonal variability remains poorly understood, which leads to uncertainty in models of global C cycling and predictions of future climate change. Here, we hypothesize that tree diversity, soil diversity, and soil properties contribute to local-scale variability of soil respiration but their relative importance changes in different seasons. To test our hypothesis, we conducted seasonal soil respiration measurements along a local-scale environmental gradient in a temperate forest in Northeast China, analyzed spatial variability of soil respiration and tested the relationships between soil respiration and a variety of abiotic and biotic factors including topography, soil chemical properties, and plant and soil diversity. We found that soil respiration varied substantially across the study site, with spatial coefficients of variation (CV) of 29.1%, 27.3% and 30.8% in spring, summer, and autumn, respectively. Soil respiration was consistently lower at high soil water content, but the influence of other factors was seasonal. In spring, soil respiration increased with tree diversity and biomass but decreased with soil fungal diversity. In summer, soil respiration increased with soil temperature, whereas in autumn, soil respiration increased with tree diversity but decreased with increasing soil nutrient content. However, soil nutrient content indirectly enhanced soil respiration via its effect on tree diversity across seasons, and forest stand structure indirectly enhanced soil respiration via tree diversity in spring. Our results highlight that substantial differences in soil respiration at local scales was jointly explained by soil properties (soil water content and soil nutrients), tree diversity, and soil fungal diversity but the relative importance of these drivers varied seasonally in our temperate forest.

Rodent-mediated seed dispersal of Korean pine in forest gaps: The importance of fine-scale spatial heterogeneity of understory vegetation

During the restoration of secondary forests in Northeast China, it is critically important to promote seed recruitment of Korean pine (Pinus koraiensis), which is highly dependent on rodents and significantly affected by spatially heterogeneous understory vegetation of forest gaps. Understanding the link between understory microhabitats and rodent-mediated seed dispersal, including post-dispersal seed predation and scatter-hoarding seed escaped predation, is essential to improve seed survival. Previous studies have focused on their qualitative relationships by roughly classifying understory vegetation characteristics, which cannot precisely predict regeneration direction. Quantifying the spatial heterogeneity of understory vegetation parameters (e.g., canopy cover, CC; gap fraction, GF) using terrestrial laser scanning (TSL) provides a vital way to determine quantitative relationships. In this study, we collected point cloud data in forest gaps with three sizes and six within-gap positions through TSL to quantify the understory microhabitats using CC and GF and integrated these parameters with spatial site data of Korean pine seeds scatter-hoarding and post-dispersal predation by rodents. The results showed that the influence of the within-gap position on the understory microhabitats was insignificant, and the spatial site selection of post-dispersal seed predation and seed storage was concentrated in the range of 0–22 m away from the seed station, irrelevant to the gap size. Considering the risk of predation by enemies and seed pilferage by competitors in forest gaps, rodents scatter-hoarded or post-dispersal predated seeds in the CC range of 0.2–0.3, and post-dispersal predated seeds less often in the CC range > 0.8. The ratio of post-dispersal seed predation to scatter-hoarding escaped predation firstly increased and then decreased along with the increase in CC and GF. Therefore, the spatial heterogeneity in understory microhabitats caused by gap treatment had an uncertain effect on rodent-mediated seed dispersal, depending on the relative ratio of post-dispersal seed predation to seed scatter-hoarding.

Variations in Growth and Photosynthetic Traits of Polyploid Poplar Hybrids and Clones in Northeast China.

To evaluate differences among 19 different ploidy hybrid poplar clones grown in northeast China, 21 traits related to growth traits and photosynthetic characteristics were detected and analyzed. Abundant phenotypic variations exist among and within populations, and these variations are the basis of forest tree genetic improvements. In this research, variance analysis showed that the traits except the net photosynthesis rate among the different ploidies and all the other traits exhibited significant differences among the ploidies or clones (p < 0.01). Estimation of phenotypic coefficients of variation, genotypic coefficients of variation, and repeatability is important for selecting superior materials. The larger the value, the greater the potential for material selection improvement. The repeatability of the different traits ranged from 0.88 to 0.99. The phenotypic and genotypic coefficients of variation of all the investigated traits ranged from 6.88% to 57.40% and from 4.85% to 42.89%, respectively. Correlation analysis showed that there were significant positive correlations between tree height, diameter, and volume. Transpiration rate, intercellular carbon dioxide concentration, and stomatal conductance were significantly positively correlated with each other but negatively correlated with instantaneous water use efficiency. Growth traits were weakly correlated with photosynthetic indexes. The rank correlation coefficient showed that most of the growth indicators reached a significant correlation level among different years (0.40-0.98), except 1-year-old tree height with 4-year-old tree height and 1-year-old ground diameter with 3-year-old tree height, which indicated the potential possibility for early selection of elite clones. Principal analysis results showed that the contribution rate of the first principal component was 46.606%, and 2-year-old tree height, 2-year-old ground diameter, 3-year-old tree height, 3-year-old ground diameter, 3-year-old diameter at breast height, 3-year-old volume, 4-year-old tree height, 4-year-old ground diameter, 4-year-old diameter at breast height, and 4-year-old volume showed higher vector values than other traits. With the method of multiple-trait comprehensive evaluation to evaluate clones, SX3.1, SY3.1, and XY4.2 were selected as elite clones, and the genetic gains of height, basal diameter, diameter at breast height, and volume of selected clones ranged from 12.85% to 64.87% in the fourth growth year. The results showed fundamental information for selecting superior poplar clones, which might provide new materials for the regeneration and improvement of forests in Northeast China.