Estimating seasonal aboveground biomass of a riparian pioneer plant community: An exploratory analysis by canopy structural data

The aboveground biomass (AGB) of vegetation is of central importance for ecosystem services by providing a measure of productivity. Models have been developed for estimating AGB via canopy structural variables in both fundamental and applied ecological studies. However, the potential of canopy structural variables for describing AGB dynamics throughout a growing season are still unclear. This study focuses on the AGB seasonal dynamics of a pioneer community, Cynodon dactylon (L.) Pers. (Bermuda grass), in a newly-formed riparian habitat at China’s Three Gorges Reservoir. The objectives are (1) to determine the most important structural variable for estimating AGB at different growing stages during the season, and (2) to develop a model that can estimate AGB at the different growing stages and using multiple structural variables. We sampled the C. dactylon community six times during the growing season from May to September 2016. Six variables were engaged in the analysis, including five canopy structural variables, i.e., canopy height (H), canopy cover (CC), leaf area index (LAI), the volume related variables V_LAI (H × LAI) and V_CC (H × CC), and one seasonal growth effect variable (SV). We conducted univariate linear regression analysis to determine the most important estimator of AGB and the best subset regression analysis were used to develop the AGB estimation model. The detected most important AGB estimator changed with different growing stages throughout a season. Canopy structural characteristics of the community are key factors for determining such changes. Cover was the most important variable for AGB estimation during the early growing season and V_LAI was the most important variable in the mid and end of the growing season. The developed best multivariate models explained an additional 11% in AGB variance on average for the different growing stages compared with the univariate models using the most important estimators. SV was found to be useful in developing an acceptance general AGB estimation model appropriate for the entire growing season. The findings of this study are expected to provide knowledge for guiding sampling work and to assist with modeling AGB and understanding the AGB seasonal dynamics in the future.     

Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City,Northwest China

Crop biomass is an important ecological indicator of growth, light use efficiency, and carbon stocks in agro-ecosystems. Light detection and ranging (LiDAR) or laser scanning has been widely used to estimate forest structural parameters and biomass. However, LiDAR is rarely used to estimate crop parameters because the short, dense canopies of crops limit the accuracy of the results. The objective of this study is to explore the potential of airborne LiDAR data in estimating biomass components of maize, namely aboveground biomass (AGB) and belowground biomass (BGB). Five biomass-related factors were measured during the entire growing season of maize. The field-measured canopy height and leaf area index (LAI) were identified as the factors that most directly affect biomass components through Pearson's correlation analysis and structural equation modeling (SEM). Field-based estimation models were proposed to estimate maize biomass components during the tasseling stage. Subsequently, the maize height and LAI over the entire study area were derived from LiDAR data and were used as input for the estimation models to map the spatial pattern of the biomass components. The results showed that the LiDAR-estimated biomass was comparable to the field-measured biomass, with root mean squared errors (RMSE) of 288.51 g/m² (AGB), and 75.81 g/m² (BGB). In conclusion, airborne LiDAR has great potential for estimating canopy height, LAI, and biomass components of maize during the peak growing season.     

The study of microclimate in response to different plant community association in tropical moist deciduous forest from northern India

The data on microclimate were collected between 2010 and 2011 in five forest communities (dry miscellaneous, sal mixed, lowland miscellaneous, teak and savannah) in a tropical moist deciduous forest in Katerniaghat Wildlife Sanctuary, Uttar Pradesh, India to compare how vegetation structure affects microclimate. Diurnal variations in microclimatic variables [photosynthetically active radiation (PAR) at forest understory level, air temperature, soil surface temperature, ambient CO₂, air absolute humidity] were measured with LI-COR 840, LI-COR 191, LI-COR 190 SZ, LI-1400-101 and LI-1400-103 (LI-COR; Lincoln, NE, USA) at centre of three 0.5 ha plots in each forest community. The diurnal trend in microclimatic parameters showed wide variations among communities. PAR at forest floor ranged from 0.0024 to 1289.9 (μmol m⁻²s⁻¹) in post-monsoon season and 0.0012 to 1877.3 (μmol m⁻²s⁻¹) in mid-winter season. Among the five communities, the highest PAR value was observed in savannah and lowest in sal mixed forest. All the forest communities received maximum PAR at forest floor between 1000 and 1200 h. The ambient air temperature ranged from 19.15 to 26.69°C in post-monsoon season and 11.31 to 23.03°C in mid-winter season. Soil temperature ranged from 13.54 to 36.88°C in post-monsoon season and 6.39 to 29.17°C in mid-winter season. Ambient CO₂ ranged from 372.16 to 899.14 μmol mol⁻¹ in post-monsoon season and 396.65 to 699.65 μmol mol⁻¹ in mid-winter season. In savannah ecosystem, diurnal trend of ambient CO₂ was totally different from rest four communities. According to Canonical correspondence analysis, PAR and ambient CO₂ are most important in establishment of forest community, among microclimatic variables.     

Estimation of big sagebrush leaf area index with terrestrial laser scanning

Accurate monitoring and quantification of the structure and function of semiarid ecosystems is necessary to improve carbon and water flux models that help describe how these systems will respond in the future. The leaf area index (LAI, m² m⁻²) is an important indicator of energy, water, and carbon exchange between vegetation and the atmosphere. Remote sensing techniques are frequently used to estimate LAI, and can provide users with scalable measurements of vegetation structure and function. We tested terrestrial laser scanning (TLS) techniques to estimate LAI using structural variables such as height, canopy cover, and volume for 42 Wyoming big sagebrush (Artemisia tridentata subsp. wyomingensis Beetle & Young) shrubs across three study sites in the Snake River Plain, Idaho, USA. The TLS-derived variables were regressed against sagebrush LAI estimates calculated using specific leaf area measurements, and compared with point-intercept sampling, a field method of estimating LAI. Canopy cover estimated with the TLS data proved to be a good predictor of LAI (r² = 0.73). Similarly, a convex hull approach to estimate volume of the shrubs from the TLS data also strongly predicted LAI (r² = 0.76), and compared favorably to point-intercept sampling (r² = 0.78), a field-based method used in rangelands. These results, coupled with the relative ease-of-use of TLS, suggest that TLS is a promising tool for measuring LAI at the shrub-level. Further work should examine the structural measures in other similar shrublands that are relevant for upscaling LAI to the plot-level (i.e., hectare) using data from TLS and/or airborne laser scanning and to regional levels using satellite-based remote sensing.     

Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system

Canopy height (H_canopy) and aboveground biomass (AGB) of crops are two basic agro-ecological indicators that can provide important indications on the growth, light use efficiency, and carbon stocks in agro-ecosystems. In this study, hundreds of stereo images with very high resolution were collected to estimate H_canopy and AGB of maize using a low-cost unmanned aerial vehicle (UAV) system. Millions of point clouds that are related to the structure from motion (SfM) were produced from the UAV stereo images through a photogrammetric workflow. Metrics that are commonly used in airborne laser scanning (ALS) were calculated from the SfM point clouds and were tested in the estimation of maize parameters for the first time. In addition, the commonly used spectral vegetation indices calculated from the UAV orthorectified image were also tested. Estimation models were established based on the UAV variables and field measurements with cross validation, during which the performance of the UAV variables was quantified. Finally, the following results were achieved: (1) the spatial patterns of maize H_canopy and AGB were predicted by a multiple stepwise linear (SWL) regression model (R² = 0.88, rRMSE = 6.40%) and a random forest regression (RF) model (R² = 0.78, rRMSE = 16.66%), respectively. (2) The UAV-estimated maize parameters were proved to be comparable to the field measurements with a mean error (ME) of 0.11 m for H_canopy, and 0.05 kg/m² for AGB. (3) The SfM point metrics, especially the mean point height (H_mean) greatly contributed to the estimation model of maize H_canopy and AGB, which can be promising indicators in the detection of maize biophysical parameters. To conclude, the variations in spectral and structural attributes for maize canopy should be simultaneously considered when only simple RGB images are available for estimating maize AGB. This study provides some suggestions on how to make full use of the low-cost and high-resolution UAV stereo images in precision agro-ecological applications and management.     

The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures

Retrieving leaf chlorophyll content at a range of spatio-temporal scales is central to monitoring vegetation productivity, identifying physiological stress and managing biological resources. However, estimating leaf chlorophyll over broad spatial extents using ground-based traditional methods is time and resource heavy. Satellite-derived spectral vegetation indices (VIs) are commonly used to estimate leaf chlorophyll content, however they are often developed and tested on broadleaf species. Relatively little research has assessed VIs for different leaf structures, particularly needle leaves which represent a large component of boreal forest and significant global ecosystems. This study tested the performance of 47 published VIs for estimating foliar chlorophyll content from different leaf and canopy structures (broadleaf and needle). Coniferous and deciduous sites were selected in Ontario, Canada, representing different dominant vegetation species (Picea mariana and Acer saccharum) and a variety of canopy structures. Leaf reflectance data was collected using an ASD Fieldspec Pro spectroradiometer (400–2500 nm) for over 300 leaf samples. Canopy reflectance data was acquired from the medium resolution imaging spectrometer (MERIS). At the canopy level, with both leaf types combined, the DD-index showed the strongest relationship with leaf chlorophyll (R² = 0.78; RMSE = 3.56 μg/cm²), despite differences in leaf structure. For needleleaf trees alone the relationship with the top VI was weaker (D_[red], R² = 0.71; RMSE = 2.32 μg/cm²). A sensitivity study using simulated VIs from physically-modelled leaf (PROSPECT) and canopy (4-Scale) reflectance was performed in order to further investigate these results and assess the impacts of different background types and leaf area index on the VIs’ performance. At the leaf level, the MNDVI8 index showed a strong linearity to changing chlorophyll and negligible difference to leaf structure/type. At canopy level, the best performing VIs were relatively consistent where LAI ≥ 4, but responded strongly to differences in background at low canopy coverage (LAI = 2). This research provides comprehensive assessments for the use of spectral indices in retrieval of spatially-continuous leaf chlorophyll content at the leaf (MTCI: R² = 0.72; p < 0.001) and canopy (DD: R² = 0.78; p < 0.001) level for resource management over different spatial and temporal scales.     

Structural indicators of richness and rarity of epiphytic lichens on Corylus avellana in two different forest types within a nature reserve in south-western Norway

Abstract:Epiphytic lichens (and some non-lichenized fungi) on 34 coppices (204 stems) ofCorylus avellana were investigated in a 140 ha study area in south-western Norway. A total of 65 species were recorded on a total bark area of 63 m². Corylus in broad-leaved deciduous forest supported more species of macrolichens, and fewer species of microlichens, than Corylus in pine forest. The macrolichen flora of the deciduous forest differed from that of the pine forest by having a rich flora of species belonging to the Lobarion alliance. OldCorylus coppices with tall stems (>8 m), large girth (>8 cm diameter at breast height) and a noticeable cover of macrolichens (>10% of bark area) supported the highest number of rare species, and overall, species of macrolichens. More than 50% cover of microlichens indicated richness and rarity of microlichens on Corylus.     

Estimation of wetland vegetation height and leaf area index using airborne laser scanning data

Wetland vegetation is a core component of wetland ecosystems. Wetland vegetation structural parameters, such as height and leaf area index (LAI) are important variables required by earth-system and ecosystem models. Therefore, rapid, accurate, objective and quantitative estimations of wetland vegetation structural parameters are essential. The airborne laser scanning (also called LiDAR) is an active remote sensing technology and can provide accurate vertical vegetation structural parameters, but its accuracy is limited by short, dense vegetation canopies that are typical of wetland environments. The objective of this research is to explore the potential of estimating height and LAI for short wetland vegetation using airborne discrete-return LiDAR data.The accuracies of raw laser points and LiDAR-derived digital elevation models (DEM) data were assessed using field GPS measured ground elevations. The results demonstrated very high accuracy of 0.09 m in raw laser points and the root mean squared error (RMSE) of the LiDAR-derived DEM was 0.15 m.Vegetation canopy height was estimated from LiDAR data using a canopy height model (CHM) and regression analysis between field-measured vegetation heights and the standard deviation (σ) of detrended LiDAR heights. The results showed that the actual height of short wetland vegetation could not be accurately estimated using the raster CHM vegetation height. However, a strong relationship was observed between the σ and the field-measured height of short wetland vegetation and the highest correlation occurred (R² = 0.85, RMSE = 0.14 m) when sample radius was 1.50 m. The accuracy assessment of the best-constructed vegetation height prediction model was conducted using 25 samples that were not used in the regression analysis and the results indicated that the model was reliable and accurate (R² = 0.84, RMSE = 0.14 m).Wetland vegetation LAI was estimated using laser penetration index (LPI) and LiDAR-predicted vegetation height. The results showed that the vegetation height-based predictive model (R² = 0.79) was more accurate than the LPI-based model (the highest R² was 0.70). Moreover, the LAI predictive model based on vegetation height was validated using the leave-one-out cross-validation method and the results showed that the LAI predictive model had a good generalization capability. Overall, the results from this study indicate that LiDAR has a great potential to estimate plant height and LAI for short wetland vegetation.     

Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest

The estimation of forest aboveground biomass (AGB) is critical for quantifying carbon stocks and essential for evaluating global carbon cycle. Many previous studies have estimated forest AGB using airborne discrete-return Light Detection and Ranging (LiDAR) data, while fewer studies predicted forest AGB using airborne full-waveform LiDAR data. The objective of this work was to evaluate the utility of airborne discrete-return and full-waveform LiDAR data in estimating forest AGB. To fulfill the objective, airborne discrete-return LiDAR-derived metrics (DR-metrics), full-waveform LiDAR-derived metrics (FW-metrics) and structure parameters (combining height metrics and canopy cover) were used to estimate forest AGB. Additionally, the combined use of DR- and FW-metrics through a nonlinear way was also evaluated for AGB estimation in a coniferous forest in Dayekou, Gansu province of China. Results indicated that both height metrics derived from discrete-return and full-waveform LiDAR data were stronger predictors of forest AGB compared with other LiDAR-derived metrics. Canopy cover derived from discrete-return LiDAR data was not sensitive to forest AGB, while canopy cover estimated by full-waveform LiDAR data (CC_WF) showed moderate correlation with forest AGB. Structure parameters derived from full-waveform LiDAR data, such as H75_FW * CC_FW, were closely related to forest AGB. In contrast, structure parameters derived from discrete-return LiDAR data were not suitable for estimating forest AGB due to the less sensitivity of canopy cover CC_DR2 to forest AGB. This research also concluded that the synergistic use of DR- and FW-metrics can provide better AGB estimates in coniferous forest.     

Foliage type specific susceptibility to ozone in Picea abies,Pinus cembra and Larix decidua at treeline: A synthesis

Cumulative ozone uptake (COU, mmol m⁻²) and O₃ flux (FO₃, nmol m⁻² s⁻¹) were related to physiological, morphological and biochemical characteristics of field-grown mature evergreen Norway spruce [Picea abies (L.) Karst.], Cembran pine [Pinus cembra L.], and deciduous European larch [Larix decidua Mill.] trees at treeline. The threshold COU causing a statistically significant decline in photosynthetic capacity (A_max) ranged between 19.6 mmol m⁻² in current-year needles of evergreen conifers and 22.0 6 mmol m⁻² in short-shoot needles of deciduous L. decidua subjected to exposure periods of ≥84 and ≥43 days, respectively. The higher O₃ sensitivity of deciduous L. decidua than of evergreen P abies and P. cembra was associated with differences in FO₃ and specific leaf area (SLA), both being significantly higher in L. decidua. FO₃ was 5.9 nmol m⁻² s⁻¹ in L. decidua and 2.7 nmol m⁻² s⁻¹ in evergreen conifers. Species-dependent differences were also related to detoxification capacity expressed through total surface area based concentrations of reduced ascorbate and α-tocopherol that both increased with SLA. Findings suggest that differences in O₃ sensitivity between evergreen and deciduous conifers can be attributed to foliage type specific differences in SLA, the latter determining physiological and biochemical characteristics of the treeline conifers.     

Analysis of the relationship between the spectral characteristics of maize canopy and leaf area index under drought stress

Maize is one of the most widespread grain crops in the world; however, more than 70% of corn in China suffers some degree of drought disaster every year. Leaf area index (LAI) is an important biophysical parameter of the vegetation canopy and has important significance for crop yield estimation. Using the data of canopy spectral reflectance and leaf area index (LAI) for maize plants experiencing different levels of soil moisture from 2011 to 2012, the characteristics of the canopy reflective spectrum and its first derivative, and their relationships to leaf area index, were analyzed. Soil moisture of the control group was about 75% while that of the drought stress treatment was about 45%. In addition, LAI retrieval models for maize were established using vegetation indices (VIs) and principal component analysis (PCA) and the models were tested using independent datasets representing different soil water contents and different developmental stages of maize. The results showed that canopy spectral reflectances were in accordance with the characteristics of green plants, under both drought stress and at different developmental stages. In the visible band, canopy reflectance for both healthy and damaged vegetation had a green-wavelength peak and a red-wavelength valley; reflectance under drought stress, especially in the green peak (about 550 nm) and the red valley (about 676 nm) was higher than in the control group. In the near-infrared band, the canopy spectral reflectance decreased substantially between 780 and 1350 nm under drought stress. Moreover, the red edge of the spectrum was shifted toward blue wavelengths. The first derivative spectrum showed a double peak phenomenon at the edge of the red band at different developmental stages: the main peak appeared between 728 and 732 nm and the minor peak at about 718 nm. The double peaks become more obvious through the growth and development of the maize, with the most notable effect during the silking and milk stages, after which it gradually decreased. During maize growth, the LAI of all plants, regardless of soil moisture conditions, increased, and the largest LAI also occurred during the silking and milk stages. During those stages, the LAI of plants under different drought stress levels was significantly lower (by 20% or more) than in normal plants with sufficient water supplies. The LAI was highly significantly correlated with canopy spectral reflectance in the bands from 350 nm to 510 nm, from 571 nm to 716 nm, and from 1450 nm to 1575 nm. Also, the LAI was significantly correlated with red edge parameters and several VIs. The Perpendicular Vegetation Index (PVI) had the best correlation with LAI, with a coefficient of determination (R²) of 0.726 for the exponential correlation. Using dependent data, a LAI monitoring model for the maize canopy was constructed using PCA and VI methods. The test results showed that both the VI and PCA methods of monitoring maize LAI could provide robust estimates, with the predicted values of LAI being significantly correlated with the measured values. The model based on PVI showed higher precision under the drought stresses, with a correlation coefficient of 0.893 (n = 27), while the model based on PCA was more precise under conditions of adequate soil moisture, with a correlation coefficient of 0.877 (n = 32). Therefore, a synthesis of the models based on both VI and PCA could be more reliable for precisely predicting LAI under different levels of drought stresses in maize.     

Leaf and green stem anatomy of the drought deciduous Mediterranean shrub Calicotome villosa (Poiret) Link. (Leguminosae)

Light and scanning electron microscopy were used to study leaf and stem fine structure of the drought deciduous green-stemmed Mediterranean shrub Calicotome villosa (Poiret) Link. (Leguminosae). Each leaf consists of three small obovate leaflets with abundant but small (16 μm length) anomocytic stomata on both surfaces. Adaxial surface exhibits more than double stomatal density (440±8 mm⁻²) than the abaxial one (185±4 mm⁻²). T-shaped trichomes (36±3 mm⁻²) are present only on the abaxial leaf surface. Leaves are unifacial, furnished with palisade parenchyma on both sides. The stem is characterized by raised ridges and grooves. Beneath the one-cell-layered epidermis sclerenchyma is found on ridges, whereas stomata and palisade chlorenchyma are found in grooves. Hairs are abundant, especially in grooves. Stem and leaf palisade chlorenchymas are structurally similar. According to these data, photosynthesis could be efficiently supported by the stem.     

The Zanclean palaeofloras around the Mont-Dore strato-volcano: A window into upper Neogene vegetation and environments in the Massif Central (Puy de Dome,France)

New Pliocene macrofloras and microfloras perfectly preserved from the Mont-Dore (Puy-de-Dôme, Massif central, France) have been reinvestigated. Samples come from different stratigraphical levels collected from three localities, Lac Chambon, La Gratade and Pont de Chocol. The ⁴⁰Ar/³⁹Ar radiometric datings bracketing the Chambon Lake and La Gratade fossil-bearing horizons give 4.46 ± 0.05 Ma and 3.94 ± 0.04 Ma, respectively, representative of the Zanclean Stage (= Brunssumian B and C), a period of the early Pliocene (5.32 to 3.6 Ma), much older than previously thought (i.e., Piacenzian). Pont de Chocol is considered to be close biostratigraphically, or even identical in age to La Gratade. Detailed morphological evaluation of leaf morphotypes completed with pollen analysis contributed to the better taxonomic knowledge of these palaeofloras. The overview focuses on floristic and phytostratigraphical characteristics of the defined stratigraphical units and their dating and correlation with previously defined palaeofloristic units of the Massif central. The study provides detailed identifications of plants representing 11 gymnosperms among which Pinaceae (pollen and winged seeds), Cupressaceae including “Taxodioid” pollen grains and Sciadopitaceae families (only pollen). Besides, different angiosperm trees and shrubs have been determined from both micro- and macro-remains. Fagaceae is the most diversified with several foliage of beech and deciduous oaks, while diversified Juglandaceae contribute mainly as abundant leaf remains of Carya, Pterocarya and Juglans; Ulmaceae with numerous leave of two Zelkova species, and also Ulmus. Various other deciduous dicotyledonous such as Alnus, Betula, Carpinus, Populus, Acer laetum and A. interrigenum are well documented. Leguminosae are recorded by a small number of leaflet imprints. Evergreen shrubs of Buxaceae (Buxus pliocenica) are scarce. All these taxa contribute to a rich biodiversity of these Pliocene assemblages. All three sites point towards riverine forest habitats dominated by hygrophilic diversified woody plants while in the surrounding plains and slopes the thermophilic elements were scarce and mesophilic taxa abundant as temperate elements. This vegetation can be compared with mixed mesophytic forests depicting a climate cooling during the two considered periods (ca. 4.46 and 3.95 Ma).     

Post-fire dynamics of woody vegetation in seasonally flooded forests (impucas) in the Cerrado-Amazonian Forest transition zone

Fire disturbance alters the structural complexity of forests, above-ground biomass stocks and patterns of growth, recruitment and mortality that determine temporal dynamics of communities. These changes may also alter forest species composition, richness, and diversity. We compared changes in plant recruitment, mortality, and turnover time over three years between burned and unburned sites of two seasonally flooded natural forest patches in a predominantly savanna landscape (regionally called ‘impucas’) in order to determine how fire alters forest dynamics and species composition. Within each impuca, 50 permanent plots (20 m × 10 m) were established and all individuals ≥5 cm diameter at breast height (DBH) identified and measured in two censuses, the first in 2007 and the second in 2010. Unplanned fires burned 30 plots in impuca 1 and 35 in impuca 2 after the first census, which enabled thereafter the comparison between burned and unburned sites. The highest mortality (8.0 and 24.3% year⁻¹ for impuca 1 and 2) and turnover time (69 and 121.5 years) were observed in the burned sites, compared to 3.7 and 5.2% year⁻¹ (mortality), and 28.4 and 40.9 years (turnover), respectively, for the unburned sites. Although these seasonally flooded impuca forests are embedded in a fire-adapted savanna landscape, the impucas vegetation appears to be sensitive to fire, with burned areas having higher mortality and turnover than unburned areas. This indicates that these forest islands are potentially at risk if regional fire frequency increases.     

Biomass storage and stand structure in a conservation unit in the Atlantic Rainforest—The role of big trees

This study represents a small-scale approach to forest structure and biomass in the Atlantic Rainforest in Brazil and provides information on an ecosystem in which there still is a lack of data in this regard.The project was carried out in the National Park “Serra dos Orgãos” in the state of Rio de Janeiro, which is one of the largest remnants of continuous forest in this area. This forest is marked by a mosaic of forest types differing in tree composition and structure. Within this heterogeneous habitat the stand structure in three investigation plots was assessed to estimate the above-ground dry biomass (AGB) for all trees with a dbh ≥ 5 cm.This study indicates the structural diversity of the Atlantic Rainforest. Trees with a dbh > 30 cm were represented by 6% of all sampled individuals (18 out of 318 trees), but contributed 72% of total estimated AGB. The results suggest that big trees in the Atlantic Rainforest may contribute more into total AGB as reported for other tropical rainforests. Small-scale structural approaches like this study are able to form an initiating framework of more detailed results and help to improve estimates on biomass amounts and therefore on carbon storage capacity.     

Environmental driving factors affecting plant biomass in natural grassland in the Loess Plateau,China

Plant biomass is a key parameter for estimating terrestrial ecosystem carbon (C) stocks, which varies greatly as a result of specific environmental conditions. Here, we tested environmental driving factors affecting plant biomass in natural grassland in the Loess Plateau, China. We found that above-ground biomass (AGB) and below-ground biomass (BGB) had a similar change trend in the order of Stipa bungeana > Leymus secalinus > Artemisia sacrorum > Artemisia scoparia, whereas shoot ratio (R/S) displayed an opposite change trend. There was a significantly positive linear relationship between the AGB and BGB, regardless of plant species (p < 0.05). Furthermore, more than 50% of the AGB were found in 20–50 cm of plant height in Compositae plants (A. sacrorum, A. scoparia), whereas over 60% of the AGB were found in 20–80 cm of plant height in Gramineae plants (S. bungeana, L. secalinus). For each plant species, more than 75% of the BGB was distributed in 0–10 cm soil depth, and 20% was distributed in 10–20 cm soil depth, while less than 5% was distributed in 20–40 cm soil depth. Further, AGB and BGB were highly affected by environmental driving factors (soil properties, plant traits, topographic properties), which were identified by the structural equation model (SEM) and the generalized additive models (GAMs). In addition, AGB was directly affected by plant traits, and BGB was directly affected by soil properties, and soil properties associated with plant traits that affected AGB and BGB through interactive effects were 9.12% and 3.59%, respectively. However, topographic properties had a weak influence on ABG and BGB (as revealed by the lowest total pathway effect). Besides, soil organic carbon (SOC), soil microbial biomass carbon (MBC), and plant height had a higher relative contribution to AGB and BGB. Our results indicate that environmental driving factors affect plant biomass in natural grassland in the Loess Plateau.     

Ground level environmental protein concentrations in various ecuadorian environments: Potential uses of aerosolized protein for ecological research

Large quantities of free protein in the environment and other bioaerosols are ubiquitous throughout terrestrial ground level environments and may be integrative indicators of ecosystem status. Samples of ground level bioaerosols were collected from various ecosystems throughout Ecuador, including pristine humid tropical forest (pristine), highly altered secondary humid tropical forest (highly altered), secondary transitional very humid forest (regrowth transitional), and suburban dry montane deforested (suburban deforested). The results explored the sensitivity of localized aerosol protein concentrations to spatial and temporal variations within ecosystems, and their value for assessing environmental change. Ecosystem specific variations in environmental protein concentrations were observed: pristine 0.32 ± 0.09 μg/m³, highly altered 0.07 ± 0.05 μg/m³, regrowth transitional 0.17 ± 0.06 μg/m³, and suburban deforested 0.09 ± 0.04 μg/m³. Additionally, comparisons of intra-environmental differences in seasonal/daily weather (dry season 0.08 ± 0.03 μg/m³ and wet season 0.10 ± 0.04 μg/m³), environmental fragmentation (buffered 0.19 ± 0.06 μg/m³ and edge 0.15 ± 0.06 μg/m³), and sampling height (ground level 0.32 ± 0.09 μg/m³ and 10 m 0.24 ± 0.04 μg/m³) demonstrated the sensitivity of protein concentrations to environmental conditions. Local protein concentrations in altered environments correlated well with satellite-based spectral indices describing vegetation productivity: normalized difference vegetation index (NDVI) (r² = 0.801), net primary production (NPP) (r² = 0.827), leaf area index (LAI) (r² = 0.410). Moreover, protein concentrations distinguished the pristine site, which was not differentiated in spectral indices, potentially due to spectral saturation typical of highly vegetated environments. Bioaerosol concentrations represent an inexpensive method to increase understanding of environmental changes, especially in densely vegetated ecosystems with high canopies or in areas needing high spatial and temporal resolution. Further research to expand understanding of the applicability of bioaerosol concentrations for environmental monitoring is supported by this pilot study.     

Species diversity of butterflies in Changbai Mountain in China

Using a modified belt transect method, we investigated the butterfly communities in five different vertical vegetation belts of Changbai Mountain in China from 1992 to 2009; these belts were broadleaf deciduous forest, coniferous–deciduous mixed forest, coniferous forest, erman’s birch forest and alp tundra. We determined the number of species and abundance of butterflies in each belt and in the coniferous–deciduous mixed forest belt, we also compared these parameters among different months. Preston’s lognormal distribution was used to model the species abundance distributions and five indicators (Shannon–Wiener diversity index (H′), Pielou uniformity index (J), Simpson predominance centralization index (C), Margalef abundance index (E) and Jaccard similarity coefficients) were used to analyze the butterfly community diversity. We found four main results. (1) Across all five vertical vegetation belts, 9641 butterflies were collected, belonging to 7 families, 98 genera and 196 species. As altitude increased, the number of butterfly genera and species gradually reduced. There was a relationship between the distribution of dominant species and the total species between each belt and the distribution of vascular plants. (2) The species abundance distribution was successfully modeled as a Preston’s lognormal distribution; the best fit was obtained when α = 0.326, the determinant coefficient of the equation was 0.74798. The species abundance distribution indicates that Changbai Mountain provides a suitable environment for butterflies; there was high species richness and an even distribution of butterfly species. There were few very common and very rare species, with most species having an intermediate abundance. (3) As altitude increased, H′ and E gradually became smaller, while C showed the opposite pattern, and J did not significantly change. The similarity coefficients analysis demonstrated a clear difference among belts; the farther apart any two belts, the smaller the similarity coefficient, indicating less similarity in the butterfly communities. The similarity coefficient between the deciduous forest and the coniferous–deciduous mixed forest belt was the largest (0.651) while that between the deciduous forest and the alp tundra was the smallest (0.141). (4) Comparison of the butterfly species communities among different months in the coniferous–deciduous mixed forest found that H′ and E showed similar directional changes, while the opposite pattern was found with C; the changes in J did not necessarily reflect the actual change in diversity.     

Seasonal abundance and activity of pill millipedes (Arthrosphaera magna) in mixed plantation and semi-evergreen forest of southern India

Seasonal occurrence and activity of endemic pill millipedes (Arthrosphaera magna) were examined in organically managed mixed plantation and semi-evergreen forest reserve in southwest India between November 1996 and September 1998. Abundance and biomass of millipedes were highest in both habitats during monsoon season. Soil moisture, conductivity, organic carbon, phosphate, potassium, calcium and magnesium were higher in plantation than in forest. Millipede abundance and biomass were about 12 and 7 times higher in plantation than in forest, respectively (P < 0.001). Their biomass increased during post-monsoon, summer and monsoon in the plantation (P < 0.001), but not in forest (P > 0.05). Millipede abundance and biomass were positively correlated with rainfall (P = 0.01). Besides rainfall, millipedes in plantation were positively correlated with soil moisture as well as temperature (P = 0.001). Among the associated fauna with pill millipedes, earthworms rank first followed by soil bugs in both habitats. Since pill millipedes are sensitive to narrow ecological changes, the organic farming strategies followed in mixed plantation and commonly practiced in South India seem not deleterious for the endangered pill millipedes Arthrosphaera and reduce the risk of local extinctions.     

Experimental evidence for a delayed response of the above-ground vegetation and the seed bank to the invasion of an annual exotic plant in deciduous forests

Invasions by alien plants significantly affect native biodiversity and ecosystem functioning. We conducted a 5-year field experiment to investigate potential effects of the annual invasive plant Impatiens glandulifera on both the native above-ground vegetation and the soil seed bank in a deciduous forest in Switzerland. Eight years after the establishment of I. glandulifera, we set up plots in patches invaded by the alien plant, in plots from which the invasive plant had been manually removed and in plots which were not yet colonized by the invasive plant. We examined plant species richness, diversity and plant species composition in the above-ground vegetation and soil seed bank in all plots one year and five years after the initiation of the experiment. The 36 plots (3 plot types × 6 replicates × 2 sites) were equally distributed over two forest sites. Neither the native above-ground vegetation nor the soil seed bank was influenced by the presence of I. glandulifera one year after the start of the field experiment. After five years, however, plant species richness of both the above-ground vegetation and the soil seed bank was reduced by 25% and 30%, respectively, in plots invaded by the alien plant compared to plots from which I. glandulifera had been removed or uninvaded plots. Furthermore, plots invaded by the alien plant had a lower total seedling density (reduction by 60%) and an altered plant species composition in the soil seed bank compared to control plots. Our field experiment indicates that negative effects of the annual invasive plant on the native above-ground vegetation and soil seed bank of deciduous forests become visible with a delay of several years.