Deciduous Broadleaf Research Articles

Forest Cover Change Detection using Geospatial Technologies in Chandaka National Park, Odisha, India

Forest plays a vital role in carbon sequestration and climate regulation. A crucial tool for managing forest, particularly in protected regions, is keeping track of how the land cover changes in natural places. Using geospatial approaches, such as remote sensing and geographic information system (GIS), the present study has revealed spatio-temporal changes in land use categories and forest cover in the Chandaka National Park of Odisha, India, throughout the period of 1980-2020. The Landsat, LISS III and Sentinel satellite images of the year 1980, 2000 and 2020 were utilized respectively to map five land use land cover categories i.e. deciduous broadleaf forest, crop land, mixed forest, scrub land and water bodies in this preserved area. The satellite images were classified using a Supervised Classification method using Maximum Likelihood algorithm and ground control points (GCPs) were used for the spatial statistical analyses. The overall accuracies of the classification method in land cover categories in year 1980, 2000 and 2020 were 90.45%, 92.76% and 94.68%, respectively. Elsewhere, in order to study land use land cover (LULC) change and loss in forest of the Chandaka National Park, LULC classification, per-pixel scales post classification and self-knowledge on the LULC change process were used. The LULC change detection results showed that deciduous broadleaf forest decreased from 179.01 sq. km (76.66%) in 1980 to 132.75 sq. km (56.85%) in 2020, while mixed forest cover increased by 8.17 sq. km (3.50%) in 1980 to 38.84 sq. km (16.63%) in 2020. Crop land, Scrub land and Water bodies were also increased by 3.34%, 3.27% and 0.07%, respectively. Two significant change processes in the area are the logging activities in several places for timber and the conversion of natural forests with plantation. Agriculture expansion in the forest’s periphery is linked to the dramatic decline in forest cover change. The decline in forest cover is also a result of the production of charcoal and lumber exploitation. Overall, our findings indicated that more public awareness and participatory forest management are necessary to preserve Chandaka National Park. This study highlights the use of geospatial technologies in understanding the changes in LULC in the Chandaka National Park.

基于集合经验模态分解去趋势的水分利用效率对气候变化响应的高程分异——以“21世纪海上丝绸之路”沿线省份为例

PDF HTML阅读 XML下载 导出引用 引用提醒 基于集合经验模态分解去趋势的水分利用效率对气候变化响应的高程分异——以“21世纪海上丝绸之路”沿线省份为例 DOI: 10.5846/stxb202107091848 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金面上项目（41971382）；江苏省科技厅研究生科研创新项目（1812000024462） Elevation differences in the response of ecosystem water use efficiency to climate change based on EEMD detrending:A case study of the provinces along the “21st Century Maritime Silk Road” Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:水分利用效率(WUE)是表征陆地碳-水循环耦合关系的重要指标，但其对气候变化响应的高程分异仍不清楚。通过集合经验模态分解(EEMD)去趋势和偏相关方法，以"21世纪海上丝绸之路"沿线省份为研究区，揭示WUE对气候变化的响应及其随高程的分异。研究结果表明：(1)研究区内WUE多年均值由中心向南北递减。不同植被类型的WUE多年均值由高到低依次为：常绿针叶林、混交林、常绿阔叶林、稀树灌木草地、耕地和城市建设用地。(2)51.11%的区域表现出均温与WUE的正相关；而81.46%地区表明温差的扩大会使得WUE增加；有近一半的研究区表明最高温的升高有利于提高WUE，而最低温的作用则相反；有67.99%的区域表明降水增多反而会导致WUE的减少。(3)在大多数土地覆盖类型，日温差和最低温主要与WUE呈正相关，而最高温和降水主要与WUE呈负相关。在常绿针叶林、耕地和城市建设用地，日均温与WUE呈负相关。在其他三种植被类型下则呈正相关。(4)在低海拔地区，均温与WUE呈负相关而在中高海拔地区则转变为正相关关系。而最高温则正好相反。降水与WUE的负相关关系系数随高度的增加而不断加强，而温差和最低温与WUE的正相关关系也随高度的增加而剧烈波动增强。 Abstract:Water use efficiency (WUE) is an important index representing the coupling relationship between terrestrial carbon and water cycle, but the elevation differences in the response of WUE to climate change remains unclear. By Ensemble empirical mode decomposition (EEMD) de-trending and partial correlation methods, this paper takes provinces along the "21st Century Maritime Silk Road" as examples to reveal the response of WUE to climate change and its differentiation with elevation. The results showed that:(1) the multiyear average WUE decreased from the center to the south and the north. The multiyear average WUE of different vegetation types from high to low was as follows:evergreen needle-leaf forest, mixed forest, evergreen broadleaf forest, deciduous broadleaf forest, savannas, croplands and urban/built-up. (2) About 51.11% of the area showed a positive correlation between average temperature and WUE, and 81.46% of the area showed that diurnal temperature and WUE were positively correlated. Nearly half of the study area indicated that the highest temperature had positive coefficient with WUE, while the lowest temperature was the opposite. In 67.99% of the area, increasing precipitation led to less WUE. (3) In most land cover types, the daily diurnal temperature range and the minimum temperature were mainly positively correlated with WUE, while the maximum temperature and precipitation were negatively correlated with WUE. In evergreen coniferous forests, croplands and urban/built-up, the daily average temperature was negatively correlated with WUE, while it was positive correlation in the other three vegetation types. (4) Average temperature had a negative coefficient with WUE in the low-altitude area, while the coefficient was positive in the mid- and high-altitude area. But it was the opposite in the relationship between the maximum temperature and WUE. The negative correlation between average precipitation and WUE became stronger with altitude rising. Meanwhile, the positive correlation between diurnal temperature and WUE, the minimum temperature and WUE also became stronger with altitude rising but with wild fluctuation. 参考文献 相似文献 引证文献

Remote Sensing of Seasonal Variation of Lai and Fapar in a Deciduous Broadleaf Forest

Remote Sensing of Seasonal Variation of Lai and Fapar in a Deciduous Broadleaf Forest

Remote Sensing of Seasonal Variation of Lai and Fapar in a Deciduous Broadleaf Forest

Remote Sensing of Seasonal Variation of Lai and Fapar in a Deciduous Broadleaf Forest

Remote Sensing of Autumn Phenology by Including Surface Soil Temperature: Algorithm Development, Calibration, and Validation

Phenology exercises a critical control on annual terrestrial ecosystem carbon uptake and indicates interaction between climate and vegetation. Solely vegetation index (VIs) is insufficient to accurately detect the end of growing season (EOS). Soil temperature (Ts) plays a modulating role in soil microbial functioning and plant growth, while its impact on EOS remains largely unknown. Hence, we compared the potential between Ts and air temperature (Ta) as indicators of EOS by using flux data from 14 deciduous broadleaf forests (DBF), 24 evergreen needleleaf forests (ENF), 7 mixed forests, and 23 none-forests (NF) over Northern temperate and boreal regions (30°-60°N) for 2001-2014. The widely used NDVI-based double logistic approach failed to capture EOS variability for these ecosystems, and we derived a new EOS algorithm with a soil temperature-based scaler, which improved the EOS modeling for all plant functional types. We found that Ts at different depths showed varied abilities for EOS modeling, and Ts at the 0-10 cm depth provided the best estimates of EOS in terms of both numbers of significant sites and the correlation coefficients (R). Estimated EOS occurred earlier by on average 2.9 days than the current MODIS phenology product for ∼56.5% pixels, especially for the ENF ecosystems (∼5.5 days). Our study suggests the usefulness of surface soil temperature for autumn leaf senescence phenology modeling, and that combination of environmental variables with the current modeling strategy can improve our understanding of autumn phenology with future climate change.

Divergent Performances of Vegetation Indices in Extracting Photosynthetic Phenology for Northern Deciduous Broadleaf Forests

Accurate estimation of photosynthetic phenology is of great importance for understanding carbon cycles. Most vegetation indices (VIs) calculated from remotely sensed reflectances represent the canopy structure and have high uncertainty in detecting the photosynthetic phenology. We compared the start/end of the photosynthetically active season (SOS/EOS) extracted from the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the near-infrared reflectance of vegetation (NIRv) and the product of NIRv and solar incident radiation (NIRvP) over northern deciduous broadleaf forests, and we used the metrics generated from solar-induced chlorophyll fluorescence (SIF), a proxy for photosynthesis, as reference. We found that the growing season extracted from the structural VIs was generally longer than the duration of photosynthetic activity retrieved from SIF: SOS derived from NDVI < NIRvP < EVI ≈ NIRv ≈ SIF and EOS from NDVI > NIRv ≈ EVI > NIRvP ≈ SIF. We investigated the mechanism underlying these phenological discrepancies using the paradigm of light-use efficiency. Our results show that the divergent performances of VIs were related to main factors limiting photosynthesis, which vary across different growth stages. The fraction of absorbed photosynthetically active radiation absorbed by chlorophyll (FAPARchl) that is well characterized by both EVI and NIRv, was the dominant factor of spring photosynthetic phenology, whilst NIRvP that is a proxy of the total amount of photosynthetically active radiation absorbed by chlorophyll (APARchl) was the dominant factor in autumn when radiation determines photosynthetic phenology. As such, we suggest that these factors be accounted for when selecting VIs for the extraction of photosynthetic phenology, i.e., EVI and NIRv are more suitable for accurate retrieval of SOS, and NIRvP is more suitable for accurate retrieval of EOS.

Nitrogen deposition stimulates decomposition via changes in the structure and function of litter food webs

Nitrogen (N) deposition poses a threat to terrestrial biodiversity and ecosystem functioning globally. However, little is known concerning how the structure and function of litter fauna communities will respond in this context. Here, a gradient of N deposition (0, 20, and 40 kg N ha−1 yr−1) was simulated in a subtropical forest of southwestern China, to assess the potential effects of increased N deposition on the trophic structure and functioning of fauna communities in decomposing leaf litters of three main subtropical plant functional groups covering a total of 18 species: six evergreen broadleaf, six deciduous broadleaf, and six coniferous trees. We found that N addition shifted the trophic structure of fauna communities in decomposing litter, and different fauna feeding guilds showed distinct response patterns. Specifically, N addition increased the abundance of predators, decreased the abundance of omnivores, while detritivores were less affected. Compared to deciduous broadleaf and coniferous litters, evergreen broadleaf litter had less complex structure of fauna communities, but it decomposed slower. Further, structural equation modeling (SEM) showed that N addition increased litter decomposition in part via changing the trophic structure of fauna communities, with a positive correlation between predators and detritivores being associated with higher decomposition. As omnivores often exhibit top-down pressure on all other trophic guilds in (sub-)tropics, our observed shifts in trophic structure and litter decomposition might be partly due to the N addition-induced declines in omnivorous ant population. Future studies should investigate the role of bottom-up and top-down forces between detritivores, predators, and omnivores in driving litter decomposition. Collectively, our findings suggest that (i) N deposition consistently shifts the trophic structure of fauna communities across litter types, and (ii) such a shift further translate into changes in the functioning of subtropical forest ecosystems.

Power law scaling relationships link canopy structural complexity and height across forest types

AbstractForest canopy structural complexity (CSC), an emergent ecosystem property, plays a critical role in controlling ecosystem productivity, resource acquisition and resource use‐efficiency; yet is poorly characterized across broad geographic scales and is difficult to upscale from the plot to the landscape.Here, we show that the relationship between canopy height and CSC can be explained using power laws by analysing lidar‐derived CSC data from 17 temperate forest sites spanning over 17 degrees of latitude. Across three plant functional types (deciduous broadleaf, evergreen needleleaf and mixed forests), CSC increases as an approximate power law of forest height. In evergreen needleleaf forests, increases in canopy height do not result in increases in complexity to the same magnitude as in other forest types.We attribute differences in the slope of height:complexity relationships among forest types to: (a) the limited diversity of crown architectures among evergreen conifer trees relative to broadleaf species; (b) differences in how vertical forest layering develops with height; and (c) competitive exclusion by needleleaf species. We show support for these potential mechanisms with an analysis of 4,324 individual trees from across 18 National Ecological Observatory Network sites showing that crown geometry‐to‐tree height relationships differ consistently between broadleaf and needleleaf species.Power law relationships between forest height and CSC have broad implications for modelling, scaling and mapping forest structural attributes. Our results suggest that forest research and management should consider the nonlinearity in scaling between forest height and CSC and that the nature of these relationships may differ by forest type.A freePlain Language Summarycan be found within the Supporting Information of this article.

Assessing the Effects of Time Interpolation of NDVI Composites on Phenology Trend Estimation

The accurate evaluation of shifts in vegetation phenology is essential for understanding of vegetation responses to climate change. Remote-sensing vegetation index (VI) products with multi-day scales have been widely used for phenology trend estimation. VI composites should be interpolated into a daily scale for extracting phenological metrics, which may not fully capture daily vegetation growth, and how this process affects phenology trend estimation remains unclear. In this study, we chose 120 sites over four vegetation types in the mid-high latitudes of the northern hemisphere, and then a Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A4 daily surface reflectance data was used to generate a daily normalized difference vegetation index (NDVI) dataset in addition to an 8-day and a 16-day NDVI composite datasets from 2001 to 2019. Five different time interpolation methods (piecewise logistic function, asymmetric Gaussian function, polynomial curve function, linear interpolation, and spline interpolation) and three phenology extraction methods were applied to extract data from the start of the growing season and the end of the growing season. We compared the trends estimated from daily NDVI data with those from NDVI composites among (1) different interpolation methods; (2) different vegetation types; and (3) different combinations of time interpolation methods and phenology extraction methods. We also analyzed the differences between the trends estimated from the 8-day and 16-day composite datasets. Our results indicated that none of the interpolation methods had significant effects on trend estimation over all sites, but the discrepancies caused by time interpolation could not be ignored. Among vegetation types with apparent seasonal changes such as deciduous broadleaf forest, time interpolation had significant effects on phenology trend estimation but almost had no significant effects among vegetation types with weak seasonal changes such as evergreen needleleaf forests. In addition, trends that were estimated based on the same interpolation method but different extraction methods were not consistent in showing significant (insignificant) differences, implying that the selection of extraction methods also affected trend estimation. Compared with other vegetation types, there were generally fewer discrepancies between trends estimated from the 8-day and 16-day dataset in evergreen needleleaf forest and open shrubland, which indicated that the dataset with a lower temporal resolution (16-day) can be applied. These findings could be conducive for analyzing the uncertainties of monitoring vegetation phenology changes.

The role of biodiversity in mitigating the effects of nutrient limitation and short-term rotations in plantations of subtropical China

Species diversity plays an essential role in enhancing ecosystem functions (EF) in both natural and plantation forests. However, we do not fully understand whether species diversity could maintain the sustainability of EFs in multiple-rotation plantations. Here, we hypothesized that tree species mixtures could mitigate declines in EFs along successive rotations, but could not maintain ecosystem multifunctionality. To test our hypothesis, we examined the effects of species diversity on four EFs, i.e., aboveground biomass (AGB), soil available nitrogen (SAN) and phosphorus (SAP), and soil organic matter (SOM), based on pure model simulation in plantations of subtropical China. The model fusion framework was set up by the integration of the process-based FORECAST and Multivariate Diversity-Interactions models. In the simulation, four local typical plantation tree species (two conifers, one evergreen broadleaf, and one deciduous N-fixing broadleaf) were selected and combined to form four monoculture and 11 mixture stands, and for each stand, the simulation was made for four 25-year rotations. The results showed that all the four EFs declined with the progress of rotations in both monoculture and mixtures, and the declining range was larger in monoculture than in mixtures in each rotation. Particularly, SAP significantly decreased while AGB, SAN, and SOM increased with diversity evenness from 0 (monoculture) to 1 (four species being equal abundant in the mixture). Overall, SAP and AGB displayed higher sensitivity to the disturbance of successive rotations compared with SAN and SOM. These results suggest that mixing species could not maintain EFs along with successive rotations because it could not alleviate SAP deficiencies in the soils resulted from the disturbances of silvicultural measures.

The Biogeography of Forest Soil Microbial Functional Diversity Responds to Forest Types across Guangxi, Southwest China

Vegetation and soil have spatial distributions at different scales, while the spatial distribution of soil microorganisms and factors driving their distribution are still unclear. We aimed to reveal the spatial pattern of microbial functional diversity and to identify its drivers in forest soils at a regional scale. Here, we performed an investigation of microbes across several forest types covering an area of 236,700 km2 in Guangxi, southwest China. We examined a total of 185 samples for soil microbial functional diversity using Biolog EcoPlates. The soil microbial functional diversity had strong spatial heterogeneity across the Guangxi region. The distribution of microorganisms in forest soils was mainly determined by total nitrogen, available N, and C:N ratio, and stand age. We found that coniferous forests, especially pine forest, exhibited lower functional diversity, but the reverse was true for deciduous broadleaf forest/mixed evergreen and deciduous broadleaf forest. Our findings suggested that a heterogeneous distribution of microbial functional diversity in forest soils is related to forest types in Guangxi, China. In conclusion, high soil microbial functional diversity is favored in subtropical forests with looser soil structure, lower soil C:N ratio, greater total soil nitrogen and available nitrogen concentration, and broad-leaved tree species.

The effect of plant size and branch traits on rainfall interception of 10 temperate tree species

AbstractRainfall interception by vegetation plays an important role in the hydrological cycle. Next to rainfall characteristics, interception is influenced by tree size, crown structure and bark morphology. How tree traits determine interception across functionally and morphologically wide‐ranging tree species is poorly understood. We determined interception ratios (interception:gross precipitation) and canopy storage capacities of seven temperate deciduous broadleaved (Acer pseudoplatanus L., Betula pendula Roth, Carpinus betulus L., Fagus sylvatica L., Populus tremula L., Sorbus aucuparia L.) and three evergreen coniferous tree species (Picea abies (L.) Karsten, Pinus sylvestris L., Pseudotsuga menziesii (Mirb.) Franco) as well as the influence of various tree traits on interception parameters. Interception was measured directly with natural rainfall by means of gravimetry on potted trees, 2–8 m tall, for seven consecutive months. Our results show that (a) the coniferous species had larger canopy storage capacities and larger interception ratios than the broadleaved species both during (summer) and outside the growing season (winter); (b) the absolute tree interception (in kg) of the broadleaved species was positively related to stem diameter at breast height, tree and crown height, maximum branch length, the total branch surface area and above ground dry weight; and (c) interception per unit crown projected area (in mm) of all species was positively related to branch length and branch surface area per unit crown projected area. These results can be used to estimate interception parameters from plant traits and to simulate interception losses of trees in a more reliable manner.

Implementation and Evaluation of a Unified Turbulence Parameterization Throughout the Canopy and Roughness Sublayer in Noah‐MP Snow Simulations

AbstractThe Noah‐MP land surface model (LSM) relies on the Monin‐Obukhov (M‐O) Similarity Theory (MOST) to calculate land‐atmosphere exchanges of water, energy, and momentum fluxes. However, MOST flux‐profile relationships neglect canopy‐induced turbulence in the roughness sublayer (RSL) and parameterize within‐canopy turbulence in an ad hoc manner. We implement a new physics scheme (M‐O‐RSL) into Noah‐MP that explicitly parameterizes turbulence in RSL. We compare Noah‐MP simulations employing the M‐O‐RSL scheme (M‐O‐RSL simulations) and the default M‐O scheme (M‐O simulations) against observations obtained from 647 Snow Telemetry (SNOTEL) stations and two AmeriFlux stations in the western United States. M‐O‐RSL simulations of snow water equivalent (SWE) outperform M‐O simulations over 64% and 69% of SNOTEL sites in terms of root‐mean‐square‐error (RMSE) and correlation, respectively. The largest improvements in skill for M‐O‐RSL occur over closed shrubland sites, and the largest degradations in skill occur over deciduous broadleaf forest sites. Differences between M‐O and M‐O‐RSL simulated snowpack are primarily attributable to differences in aerodynamic conductance for heat underneath the canopy top, which modulates sensible heat flux. Differences between M‐O and M‐O‐RSL within‐canopy and below‐canopy sensible heat fluxes affect the amount of heat transported into snowpack and hence change snowmelt when temperatures are close to or above the melting point. The surface energy budget analysis over two AmeriFlux stations shows that differences between M‐O and M‐O‐RSL simulations can be smaller than other model biases (e.g., surface albedo). We intend for the M‐O‐RSL physics scheme to improve performance and uncertainty estimates in weather and hydrological applications that rely on Noah‐MP.

Estimation of CO2 flux components over northern hemisphere forest ecosystems by using random forest method through temporal and spatial data scanning procedures.

Modeling CO2 flux components is an important task in ecosystem analysis and terrestrial studies. Net ecosystem exchange (NEE), ecosystem respiration (R), and gross primary production (GPP) are three CO2 flux components. Despite the ecosystem land cover characteristics, climatic factors can make considerable impact on quantity and mechanism of these components. Nevertheless, such climatic factors are not available in most of the areas, especially in developing regions. Therefore, obtaining the models that can exempt using locally recorded variables would be of great importance. A modeling study was carried out here to simulate CO2 flux components using soft computing-based random forest (RF) model in both local and external (spatial) scales, assessed by k-fold validation procedure. Data from 11 sites located in three forest ecosystems, e.g. deciduous broad leaf (DBF), evergreen needle leaf (ENF), and mixed forest (MF), were used to simulate the flux components. The obtained results showed that the temperature-related parameters (e.g., air and soil temperature, vapor pressure deficit) along with the net radiation play key role in determining the flux components in all studied ecosystems. It was confirmed that a chronologic scan of the available patterns is needed for a thorough assessment of the performance accuracy of the local models. The external models provided promising results when compared with the locally trained models. This is a very great step forward in estimating CO2 flux components under data scarcity conditions.

Evaluation of Clumping Effects on the Estimation of Global Terrestrial Evapotranspiration

In terrestrial ecosystems, leaves are aggregated into different spatial structures and their spatial distribution is non-random. Clumping index (CI) is a key canopy structural parameter, characterizing the extent to which leaf deviates from the random distribution. To assess leaf clumping effects on global terrestrial ET, we used a global leaf area index (LAI) map and the latest version of global CI product derived from MODIS BRDF data as well as the Boreal Ecosystem Productivity Simulator (BEPS) to estimate global terrestrial ET. The results show that global terrestrial ET in 2015 was 511.9 ± 70.1 mm yr−1 for Case I, where the true LAI and CI are used. Compared to this baseline case, (1) global terrestrial ET is overestimated by 4.7% for Case II where true LAI is used ignoring clumping; (2) global terrestrial ET is underestimated by 13.0% for Case III where effective LAI is used ignoring clumping. Among all plant functional types (PFTs), evergreen needleleaf forests were most affected by foliage clumping for ET estimation in Case II, because they are most clumped with the lowest CI. Deciduous broadleaf forests are affected by leaf clumping most in Case III because they have both high LAI and low CI compared to other PFTs. The leaf clumping effects on ET estimation in both Case II and Case III is robust to the errors in major input parameters. Thus, it is necessary to consider clumping effects in the simulation of global terrestrial ET, which has considerable implications for global water cycle research.

Estimations of forest water retention across China from an observation site-scale to a national-scale

Hydrological models or remote sensing methods are often used to estimate water retention amounts and to analyze large spatial variations in water retention across large scales. However, the accuracies of hydrological models and remote sensing data are far lower than those of site-observational data. Here, we used 1045 observational sites of forest ecosystem across China and a random forest (RF) model for more accurate spatial prediction of canopy interception amount (CIA), litter maximum water-holding amount (LWHA), soil water storage amount (SSA), and forest water retention amount (WRA) of China. We found that the total forest WRA in China was 2325.87 × 108 m3, and the CIA, LWHA and SSA contributed 21.24%, 5.37% and 73.39%, respectively, to the WRA. The forest WRA in the basins of southern China including the Yangtze River Basin (YTRB), Songhua River Basin (SHRB), Southwest Rivers Basin (SWRB) and Pearl River Basin (PRB) accounted for 78.33% of the total forest WRA. The WRAs of subtropical needleleaf forest, temperate deciduous broadleaf forest, subtropical and tropical mountainous needleleaf forest, subtropical evergreen broadleaf forest, and cold and temperate mountainous needleleaf forest accounted for 50.61% of the total WRA in Chinese forests. The WRAs of cold and temperate forest types were relatively higher in the SHRB, Liao River Basin (LRB), Northwest Rivers Basin (NWRB), Hai River Basin (HRB) and Yellow River Basin (YRB) than in other basins, and the WRAs of subtropical and tropical forests types were relatively higher in the YTRB, Southeast Rivers Basin (SERB), SWRB, and PRB than in the other basins. This observation-based assessment can provide insight into spatial variations in different layers of the WRA including canopy, litter, and soil which can be used for forest resource management in China.

Different Temporal Stability and Responses to Droughts between Needleleaf Forests and Broadleaf Forests in North China during 2001–2018

Droughts can affect the physiological activity of trees, damage tissues, and even trigger mortality, yet the response of different forest types to drought at the decadal time scale remains uncertain. In this study, we used two remote sensing-based vegetation products, the MODIS enhanced vegetation index (EVI) and MODIS gross primary productivity (GPP), to explore the temporal stability of deciduous needleleaf forests (DNFs) and deciduous broadleaf forests (DBFs) in droughts and their legacy effects in North China from 2001 to 2018. The results of both products showed that the temporal stability of DBFs was consistently much higher than that of DNFs, even though the DBFs experienced extreme droughts and the DNFs did not. The DBFs also exhibited similar patterns in their legacy effects from droughts, with these effects extending up to 4 years after the droughts. These results indicate that DBFs have been better acclimated to drought events in North China. Furthermore, the results suggest that the GPP was more sensitive to water variability than EVI. These findings will be helpful for forest modeling, management, and conservation.

Regulation of soil phosphorus availability and composition during forest succession in subtropics

Although phosphorus (P) is a limiting nutrient for plant growth in subtropical forests, the effects of forest succession on soil P dynamics, which in turn influences P availability, are unclear. The objective was to access the impacts of forest succession on P fractions of different availability (Hedley sequential fractionation) in highly weathered subtropical soils. We compared the P dynamics and availability under the chronosequence of forest succession from four stages: i) Cunninghamia lanceolata plantation, ii) through mixed broadleaf-conifer, iii) deciduous broadleaved, and finally iv) evergreen broadleaved forest. The soil P was dominated by stable P fractions (69–76%) in all successional stages. Forest succession increased total P content from plantation (199 mg kg−1) to evergreen broadleaved forest (253 mg kg−1), whereas P reached the peak in deciduous broadleaved forest and then remains stable due to balance between input with litter and litter decomposition and tree uptake. Stable P (non-available P) increased for 31–39% with forest succession because soil acidification led to more Fe and Al (oxyhydr)oxides strongly bounding P. Moderately labile P (moderately available P) contents under deciduous and evergreen broadleaved forests were higher than under plantation and mixed forest due to organic matter accumulation. However, labile (easily available) P content was reduced 35–50% by succession because of P removal by plant uptake. Available P content reached the peak under deciduous broadleaved forest (64–81 mg kg−1) and decreased again, indicating that forest ecosystem transit from P acquiring to P recycling system (litter input and plant uptake of mineralized P). Fine root biomass was the primary driver that controlled total, moderately labile and stable P contents during forest succession. Available P increased with soil organic carbon (SOC), suggesting that organic matter is crucial to maintain P availability. The C/P ratio of litter was the primary driver decreasing available P because litter decomposition released P is the main source determining P availability in soil. The increase of moderately labile P following forest succession played a crucial role for accumulation of available P. These results suggest that forest succession increases soil P availability until deciduous broadleaved forest. Therefore, strong measures to facilitate succession to the deciduous broadleaved forest stage should be a key approach to increase long-term soil P availability in subtropics.

Plant trait filtering is stronger in the herb layer than in the tree layer in Greek mountain forests

We studied the differentiation among plant communities of deciduous broadleaved and mountain coniferous forests in terms of functional diversity and identity at a regional scale (northern and central Greece). We asked if patterns of functional differentiation among communities are consistent between the overstorey and understorey layers and if they can be influenced by deep past environmental conditions. Functional Richness (FRic) and Functional Dispersion (FDis), as well as their standardized effect sizes, were employed to assess the multivariate functional diversity of the community types. In contrast, single-trait Community Weighted Means (CWMs) were used as surrogates of functional identity. The aforementioned indices were calculated for three datasets, namely all the vascular plant taxa found in individual vegetation plots (total community), all phanerophyte (tree and shrub) taxa (overstorey) and all non-phanerophyte vascular plant taxa (understorey). We found that community types and especially four broad forest types (beech, ravine, pine and oak forests) are well differentiated in terms of functional composition (identity), as indicated by Non-Metric Multidimensional Scaling (NMDS). After conducting an NMDS for the three datasets, functional identity based on the total floristic composition was found to be the best discriminator of the studied communities. However, contrasting patterns were found for some specific traits or their categories between overstorey and understorey layers. The patterns of functional diversity of the community types (based on multivariate indices), revealed by calculating the standardized effect sizes of FRic and FDis based on the richness null model, did not differ substantially from random expectations for most of the studied community types when the dataset of all the vascular plant taxa was analyzed. However, the patterns revealed for the overstorey layer differed from those for the understorey layer. For the latter layer, the clustered structure was revealed in many community types based on the ses.FDis metric. Indications of deep past influence on the functional composition were found for certain community types (i.e. ravine forests) based on single-trait metrics, but no indication of such influence was found based on multivariate indices. Our findings highlight the complementarity and the additive explanatory value of the simultaneous use of single- and multi-trait approaches and their application to different layers in forests.

Comparative Transcriptome Analysis Revealed Candidate Genes Potentially Related to Desiccation Sensitivity of Recalcitrant Quercus variabilis Seeds.

Chinese cork oak (Quercus variabilis) is a widely distributed and highly valuable deciduous broadleaf tree from both ecological and economic perspectives. Seeds of this species are recalcitrant, i.e., sensitive to desiccation, which affects their storage and long-term preservation of germplasm. However, little is known about the underlying molecular mechanism of desiccation sensitivity of Q. variabilis seeds. In this study, the seeds were desiccated with silica gel for certain days as different treatments from 0 (Control) to 15 days (T15) with a gradient of 1 day. According to the seed germination percentage, four key stages (Control, T2, T4, and T11) were found. Then the transcriptomic profiles of these four stages were compared. A total of 4,405, 4,441, and 5,907 differentially expressed genes (DEGs) were identified in T2 vs. Control, T4 vs. Control, and T11 vs. Control, respectively. Among them, 2,219 DEGs were overlapped in the three comparison groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these DEGs were enriched into 124 pathways, such as “Plant hormone signal transduction” and “Glycerophospholipid metabolism”. DEGs related to hormone biosynthesis and signal transduction (ZEP, YUC, PYR, ABI5, ERF1B, etc.), stress response proteins (LEA D-29, HSP70, etc.), and phospholipase D (PLD1) were detected during desiccation. These genes and their interactions may determine the desiccation sensitivity of seeds. In addition, group specific DEGs were also identified in T2 vs. Control (PP2C62, UNE12, etc.), T4 vs. Control (WRKY1-like, WAK10, etc.), and T11 vs. Control (IBH1, bZIP44, etc.), respectively. Finally, a possible work model was proposed to show the molecular regulation mechanism of desiccation sensitivity in Q. variabilis seeds. This is the first report on the molecular regulation mechanism of desiccation sensitivity of Q. variabilis seeds using RNA-Seq. The findings could make a great contribution to seed storage and long-term conservation of recalcitrant seeds in the future.