Natural Forest Biomass Estimation Based on Plantation Information Using PALSAR Data

Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ⁰) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ⁰ showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ⁰ were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R² = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE  = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal.     

Temperature-Dependent Fecundity and Life Table of the Fennel Aphid Hyadaphis foeniculi (Passerini) (Hemiptera: Aphididae)

Hyadaphis foeniculi (Passerini) (Hemiptera: Aphididae) is a cosmopolitan species and the main pest of fennel in northeastern Brazil. Understanding the relationship between temperature variations and the population growth rates of H. foeniculi is essential to predict the population dynamics of this aphid in the fennel crop. The aim of this study was to measure the effect of constant temperature on the adult prereproductive period and the life table fertility parameters (infinitesimal increase ratio (r_m), gross reproduction rate (GRR), net reproduction rate (R₀), finite increase ratio (λ), generation time (GT), the time required for the population to double in the number of individuals (DT), and the reproduction value (RV_x)) of the fennel pest H. foeniculi. The values of lx (survival of nymphs at age x) increased as the temperature rose from 15 to 28°C and fell at 30°C, whereas mx (number of nymphs produced by each nymph of age x) increased from 15 to 25°C and fell at 28 and 30°C. The net reproduction rates (R₀) of populations of H. foeniculi increased with temperature and ranged from 1.9 at 15°C to 12.23 at 28°C for each generation. The highest population increase occurred with the apterous aphids at 28°C. The rate of population increase per unit time (r_m) (day) ranged from 0.0033 (15°C) to 0.1995 (28°C). The highest values of r_m were recorded at temperatures of 28°C and 30°C. The r_m values were a good fit to the models tested, with R² > 0.91 and R² _adj > 0.88. The models tested (Davidson, Sharpe and DeMichele modified by Schoolfield et al., Logan et al., Lamb, and Briere et al.) were very good fits for the r_m values observed, with R² > 0.91 and R² _adj > 0.88. The only exception was the Davidson model. Of the parameters studied, the reproductive capacity was higher in the apterous aphids, with the unique exception of daily fecundity at 28°C, which was higher in the alate aphids of H. foeniculi. Parameters relating to the age-specific fertility table for H. foeniculi were heavily influenced by temperature, with the highest biotic potential and population growth capacity found at 34°C. Therefore, the results obtained in this study could be of practical significance for predicting outbreaks of fennel aphids and improving the management of this aphid in fennel crops.     

Genetic differentiation and signatures of local adaptation revealed by RADseq for a highly dispersive mud crab Scylla olivacea (Herbst, 1796) in the Sulu Sea

Connectivity of marine populations is shaped by complex interactions between biological and physical processes across the seascape. The influence of environmental features on the genetic structure of populations has key implications for the dynamics and persistence of populations, and an understanding of spatial scales and patterns of connectivity is crucial for management and conservation. This study employed a seascape genomics approach combining larval dispersal modeling and population genomic analysis using single nucleotide polymorphisms (SNPs) obtained from RADseq to examine environmental factors influencing patterns of genetic structure and connectivity for a highly dispersive mud crab Scylla olivacea (Herbst, 1796) in the Sulu Sea. Dispersal simulations reveal widespread but asymmetric larval dispersal influenced by persistent southward and westward surface circulation features in the Sulu Sea. Despite potential for widespread dispersal across the Sulu Sea, significant genetic differentiation was detected among eight populations based on 1,655 SNPs (F_ST = 0.0057, p < .001) and a subset of 1,643 putatively neutral SNP markers (F_ST = 0.0042, p < .001). Oceanography influences genetic structure, with redundancy analysis (RDA) indicating significant contribution of asymmetric ocean currents to neutral genetic variation (Radj2 = 0.133, p = .035). Genetic structure may also reflect demographic factors, with divergent populations characterized by low effective population sizes (N _e < 50). Pronounced latitudinal genetic structure was recovered for loci putatively under selection (F_ST = 0.2390, p < .001), significantly correlated with sea surface temperature variabilities during peak spawning months for S. olivacea (Radj2 = 0.692–0.763; p < .050), suggesting putative signatures of selection and local adaptation to thermal clines. While oceanography and dispersal ability likely shape patterns of gene flow and genetic structure of S. olivacea across the Sulu Sea, the impacts of genetic drift and natural selection influenced by sea surface temperature also appear as likely drivers of population genetic structure. This study contributes to the growing body of literature documenting population genetic structure and local adaptation for highly dispersive marine species, and provides information useful for spatial management of the fishery resource.     

Spatio-Temporal Variation in Vegetation Biomass and Its Relationships with Climate Factors in the Xilingol Grasslands,Northern China

Knowledge about grassland biomass and its dynamics is critical for studying regional carbon cycles and for the sustainable use of grassland resources. In this study, we investigated the spatio-temporal variation of biomass in the Xilingol grasslands of northern China. Field-based biomass samples and MODIS time series data sets were used to establish two empirical models based on the relationship of the normalized difference vegetation index (NDVI) with above-ground biomass (AGB) as well as that of AGB with below-ground biomass (BGB). We further explored the climatic controls of these variations. Our results showed that the biomass averaged 99.01 Tg (1 Tg=10¹² g) over a total area of 19.6×10⁴ km² and fluctuated with no significant trend from 2001 to 2012. The mean biomass density was 505.4 g/m², with 62.6 g/m² in AGB and 442.8 g/m² in BGB, which generally decreased from northeast to southwest and exhibited a large spatial heterogeneity. The year-to-year AGB pattern was generally consistent with the inter-annual variation in the growing season precipitation (GSP), showing a robust positive correlation (R²=0.82, P<0.001), but an opposite coupled pattern was observed with the growing season temperature (GST) (R²=0.61, P=0.003). Climatic factors also affected the spatial distribution of AGB, which increased progressively with the GSP gradient (R²=0.76, P<0.0001) but decreased with an increasing GST (R²=0.70, P<0.0001). An improved moisture index that combined the effects of GST and GSP explained more variation in AGB than did precipitation alone (R²=0.81, P<0.0001). The relationship between AGB and GSP could be fit by a power function. This increasing slope of the GSP–AGB relationships along the GSP gradient may be partly explained by the GST–GSP spatial pattern in Xilingol. Our findings suggest that the relationships between climatic factors and AGB may be scale-dependent and that multi-scale studies and sufficient long-term field data are needed to examine the relationships between AGB and climatic factors.     

Historical and projected carbon balance of mature black spruce ecosystems across North America: the role of carbon–nitrogen interactions

The role of carbon (C) and nitrogen (N) interactions on sequestration of atmospheric CO₂ in black spruce ecosystems across North America was evaluated with the Terrestrial Ecosystem Model (TEM) by applying parameterizations of the model in which C–N dynamics were either coupled or uncoupled. First, the performance of the parameterizations, which were developed for the dynamics of black spruce ecosystems at the Bonanza Creek Long-Term Ecological Research site in Alaska, were evaluated by simulating C dynamics at eddy correlation tower sites in the Boreal Ecosystem Atmosphere Study (BOREAS) for black spruce ecosystems in the northern study area (northern site) and the southern study area (southern site) with local climate data. We compared simulated monthly growing season (May to September) estimates of gross primary production (GPP), total ecosystem respiration (RESP), and net ecosystem production (NEP) from 1994 to 1997 to available field-based estimates at both sites. At the northern site, monthly growing season estimates of GPP and RESP for the coupled and uncoupled simulations were highly correlated with the field-based estimates (coupled: R ²= 0.77, 0.88 for GPP and RESP; uncoupled: R ² = 0.67, 0.92 for GPP and RESP). Although the simulated seasonal pattern of NEP generally matched the field-based data, the correlations between field-based and simulated monthly growing season NEP were lower (R ² = 0.40, 0.00 for coupled and uncoupled simulations, respectively) in comparison to the correlations between field-based and simulated GPP and RESP. The annual NEP simulated by the coupled parameterization fell within the uncertainty of field-based estimates in two of three years. On the other hand, annual NEP simulated by the uncoupled parameterization only fell within the field-based uncertainty in one of three years. At the southern site, simulated NEP generally matched field-based NEP estimates, and the correlation between monthly growing season field-based and simulated NEP (R ² = 0.36, 0.20 for coupled and uncoupled simulations, respectively) was similar to the correlations at the northern site. To evaluate the role of N dynamics in C balance of black spruce ecosystems across North America, we simulated historical and projected C dynamics from 1900 to 2100 with a global-based climatology at 0.5° resolution (latitude × longitude) with both the coupled and uncoupled parameterizations of TEM. From analyses at the northern site, several consistent patterns emerge. There was greater inter-annual variability in net primary production (NPP) simulated by the uncoupled parameterization as compared to the coupled parameterization, which led to substantial differences in inter-annual variability in NEP between the parameterizations. The divergence between NPP and heterotrophic respiration was greater in the uncoupled simulation, resulting in more C sequestration during the projected period. These responses were the result of fundamentally different responses of the coupled and uncoupled parameterizations to changes in CO₂ and climate.     

Female and male Eurasian lynx have distinct spatial tactics at different life‐history stages in a high‐density population

Knowledge regarding the spatial behavior of the Eurasian lynx is mainly inferred from populations in Europe. We used GPS telemetry to record the spatial behavior of nine individuals in northwestern Anatolia obtaining eleven home ranges (HRs). Analyses revealed the smallest mean HR sizes (n_{HR ♀}  = 4) at 57 km² (95% kernel utilization distribution, KUD) and 56 km² (95% minimum convex polygon, MCP), ever reported for adult female Eurasian lynx. Adult males either occupied small permanent territories (n_HR♂._T = 2), with a mean of 176 km² (95% KUD) and 150 km² (95% MCP), or were residents without territories (floaters, n_HR♂. _F  = 2) roaming across large, stable HRs with a mean size of 2,419 km² (95% KUD) and 1,888 km² (95% MCP), comparable to HR sizes of Scandinavian lynx populations. Three disperser subadult males did not hold stable HRs (mean 95% KUD = 203 km², mean 95% MCP = 272 km²). At 4.9 individuals per 100 km², population density was one of the highest recorded, suggesting that the presence of adult male floaters was a consequence of a landscape fully occupied by territorials and revealing a flexibility of spatial behavior of Eurasian lynx not previously recognized. Such a high population density, small HRs, and behavioral flexibility may have been aided by the legal protection from and apparent low levels of poaching of this population. The observed spatial tactics are unlikely to be seen in most of the previously studied Eurasian lynx populations, as they either suffer medium to high levels of human‐caused mortality or were unlikely to be at carrying capacity. For effective and appropriate conservation planning, data from felid populations in a reasonably natural state such as ours, where space, density, prey, and pathogens are likely to be the key drivers of spatial dynamics, are therefore essential.     

Marine Mammal Strandings and Environmental Changes: A 15-Year Study in the St. Lawrence Ecosystem

Understanding the effects of climatic variability on marine mammals is challenging due to the complexity of ecological interactions. We used general linear models to analyze a 15-year database documenting marine mammal strandings (1994–2008; n = 1,193) and nine environmental parameters known to affect marine mammal survival, from regional (sea ice) to continental scales (North Atlantic Oscillation, NAO). Stranding events were more frequent during summer and fall than other seasons, and have increased since 1994. Poor ice conditions observed during the same period may have affected marine mammals either directly, by modulating the availability of habitat for feeding and breeding activities, or indirectly, through changes in water conditions and marine productivity (krill abundance). For most species (75%, n = 6 species), a low volume of ice was correlated with increasing frequency of stranding events (e.g. R² _adj = 0.59, hooded seal, Cystophora cristata). This likely led to an increase in seal mortality during the breeding period, but also to increase habitat availability for seasonal migratory cetaceans using ice-free areas during winter. We also detected a high frequency of stranding events for mysticete species (minke whale, Balaenoptera acutorostrata) and resident species (beluga, Delphinapterus leucas), correlated with low krill abundance since 1994. Positive NAO indices were positively correlated with high frequencies of stranding events for resident and seasonal migratory cetaceans, as well as rare species (R² _adj = 0.53, 0.81 and 0.34, respectively). This contrasts with seal mass stranding numbers, which were negatively correlated with a positive NAO index. In addition, an unusual multiple species mortality event (n = 114, 62% of total annual mortality) in 2008 was caused by a harmful algal bloom. Our findings provide an empirical baseline in understanding marine mammal survival when faced with climatic variability. This is a promising step in integrating stranding records to monitor the consequences of environmental changes in marine ecosystems over long time scales.     

Identification of NF-κB and PLCL2 as new susceptibility genes and highlights on a potential role of IRF8 through interferon signature modulation in systemic sclerosis

IntroductionSystemic sclerosis (SSc) and primary biliary cirrhosis (PBC) are rare polygenic autoimmune diseases (AIDs) characterized by fibroblast dysfunction. Furthermore, both diseases share some genetic bases with other AIDs, as evidenced by autoimmune gene pleiotropism. The present study was undertaken to investigate whether single-nucleotide polymorphisms (SNPs) identified by a large genome-wide association study (GWAS) in PBC might contribute to SSc susceptibility.MethodsSixteen PBC susceptibility SNPs were genotyped in a total of 1,616 patients with SSc and 3,621 healthy controls from two European populations (France and Italy).ResultsWe observed an association between PLCL2 rs1372072 (odds ratio (OR) = 1.22, 95% confidence interval (CI) 1.12 to 1.33, P_adj = 7.22 × 10⁻⁵), nuclear factor-kappa-B (NF-κB) rs7665090 (OR = 1.15, 95% CI 1.06 to 1.25, P_adj = 0.01), and IRF8 rs11117432 (OR = 0.75, 95% CI 0.67 to 0.86, P_adj = 2.49 × 10⁻⁴) with SSc susceptibility. Furthermore, phenotype stratification showed an association between rs1372072 and rs11117432 with the limited cutaneous subgroup (lcSSc) (P_adj = 4.45 × 10⁻⁴ and P_adj = 0.001), whereas rs7665090 was associated with the diffuse cutaneous subtype (dcSSc) (P_adj = 0.003). Genotype-mRNA expression correlation analysis revealed that the IRF8 protective allele was associated with increased interferon-gamma (IFN-γ) expression (P = 0.03) in patients with SSc but decreased type I IFN (IFIT1) expression in patients and controls (P = 0.02). In addition, we found an epistatic interaction between NF-κB and IRF8 (OR = 0.56, 95% CI 0.00 to 0.74, P = 4 × 10⁻⁴) which in turn revealed that the IRF8 protective effect is dependent on the presence of the NF-κB susceptibility allele.ConclusionsAn analysis of pleiotropic genes identified two new susceptibility genes for SSc (NF-κB and PLCL2) and confirmed the IRF8 locus. Furthermore, the IRF8 variant influenced the IFN signature, and we found an interaction between IRF8 and NF-κB gene variants that might play a role in SSc susceptibility.

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The online version of this article (doi:10.1186/s13075-015-0572-y) contains supplementary material, which is available to authorized users.     

A Genome-Wide Association Study Identifies Potential Susceptibility Loci for Hirschsprung Disease

Hirschsprung disease (HSCR) is a congenital and heterogeneous disorder characterized by the absence of intramural nervous plexuses along variable lengths of the hindgut. Although RET is a well-established risk factor, a recent genome-wide association study (GWAS) of HSCR has identified NRG1 as an additional susceptibility locus. To discover additional risk loci, we performed a GWAS of 123 sporadic HSCR patients and 432 unaffected controls using a large-scale platform with coverage of over 1 million polymorphic markers. The result was that our study replicated the findings of RET-CSGALNACT2-RASGEF1A genomic region (_rawP = 5.69×10⁻¹⁹ before a Bonferroni correction; _corrP = 4.31×10⁻¹³ after a Bonferroni correction) and NRG1 as susceptibility loci. In addition, this study identified SLC6A20 (_adjP = 2.71×10⁻⁶), RORA (_adjP = 1.26×10⁻⁵), and ABCC9 (_adjP = 1.86×10⁻⁵) as new potential susceptibility loci under adjusting the already known loci on the RET-CSGALNACT2-RASGEF1A and NRG1 regions, although none of the SNPs in these genes passed the Bonferroni correction. In further subgroup analysis, the RET-CSGALNACT2-RASGEF1A genomic region was observed to have different significance levels among subgroups: short-segment (S-HSCR, _corrP = 1.71×10⁻⁵), long-segment (L-HSCR, _corrP = 6.66×10⁻⁴), and total colonic aganglionosis (TCA, _corrP>0.05). This differential pattern in the significance level suggests that other genomic loci or mechanisms may affect the length of aganglionosis in HSCR subgroups during enteric nervous system (ENS) development. Although functional evaluations are needed, our findings might facilitate improved understanding of the mechanisms of HSCR pathogenesis.     

Unmanned aerial systems accurately map rangeland condition indicators in a dryland savannah

Dry savannahs are highly sensitive to climate change and under intense anthropogenic pressure. Therefore, the methods for assessing their status should be easy and repeatable. Monitoring through satellite data and field measurements are limited in accurately assessing the spatiotemporal dynamics of ecosystems. Fortunately, emerging technologies like Unmanned Aerial Systems (UAS) allow to transcend these limitations. But their calibration with field data for application in rangelands is still relatively new and less common than for example in precision agriculture. In this study we developed a drone-based workflow for mapping the condition of rangelands in dryland savannah. We evaluated how accurately and efficiently the two common indicators (i.e., potential forage biomass and rangeland cover type) of rangeland condition can be estimated from drone imagery across a range of conditions (i.e., highly degraded to healthy rangelands). To develop the drone-based potential forage biomass model we tested the accuracy of four vegetation indices to predict field biomass, with the optimized soil adjusted vegetation index (OSAVI) showing the highest prediction accuracy (R² = 0.89 and RMSE = 194.05). The OSAVI-based model yielded a significant strong relationship (R² = 0.80, p < 0.001) between predicted and field observed potential forage biomass across the rangeland system. For land cover, we applied a decision tree classification based on thresholds determined using data mining, with a mean overall accuracy of 95.8%. The drone-based estimates of bare cover, herbaceous cover and woody cover showed strong agreements (R² ranging between 0.86 and 0.97) with the two image-truthing methods (line-point intercept and visual estimations) tested. We show that the drone-based approach is more efficient, unbiased, and repeatable than the field methods. Based on these results, the drone-based workflow presented here offers a reproducible, accurate and efficient approach for near-real time monitoring of rangeland condition at a landscape level. This may assist with climate-adapted management to prevent further land degradation and associated threats to biodiversity and human livelihoods.     

Polymorphism in miR-31 and miR-584 binding site in the angiotensinogen gene differentially influences body fat distribution in both sexes

Angiotensinogen (AGT), its active fragments and microRNA-31 (miR-31) play an important role in adipocyte differentiation. AGT contains a miR-31 polymorphic binding site. We hypothesize that the rs7079 polymorphism in the miR-31/584 binding site of the AGT gene could influence body fat distribution. A total of 751 subjects (195 men, 556 women) were enrolled in the study. The rs7079 genotypes were determined by qRT-PCR. Anthropometric measurements were taken on all subjects, who were subsequently divided into two groups: obese (>30 kg m⁻²) and non-obese (<30 kg m⁻²). Linear regression models were created to determine the contributions of sex, obesity status and rs7079 to all measured parameters. Adding the rs7079 genotype significantly contributed to the linear regression model for waist circumference (p = 0.013), hip circumference (p = 0.018) and supraspinal skin-fold thickness (p = 1 × 10⁻³). Differences between sexes and between the obese and non-obese groups were observed. Waist circumference was lower in men carrying the A allele (p = 0.022); hip circumference was higher only in obese women carrying the A allele (p = 0.015). While men carrying the A allele had lower supraspinal skin-fold thickness (p = 0.022), this parameter was found to be higher in A allele carrying women (p = 3 × 10⁻³). The higher total sum of skin-fold thickness in A allele carrying women was restricted to obese individuals (p = 0.028). The presence of the A allele was associated with both lower tricipital skin-fold thickness in non-obese women (p = 0.023) and a trend of higher thickness in non-obese men (p = 0.065). Significant associations of rs7079 in the AGT gene and body fat distribution were observed. The distribution followed opposing patterns in both sexes.     

Small Changes in Climate Can Profoundly Alter the Dynamics and Ecosystem Services of Tropical Crater Lakes

African tropical lakes provide vital ecosystem services including food and water to some of the fastest growing human populations, yet they are among the most understudied ecosystems in the world. The consequences of climate change and other stressors on the tropical lakes of Africa have been informed by long-term analyses, but these studies have largely focused on the massive Great Rift Valley lakes. Our objective was to evaluate how recent climate change has altered the functioning and services of smaller tropical lakes, which are far more abundant on the landscape. Based on a paired analysis of 20 years of high-resolution water column data and a paleolimnological record from a small crater lake in western Uganda, we present evidence that even a modest warming of the air (∼0.9°C increase over 20 years) and changes in the timing and intensity of rainfall can have significant consequences on the dynamics of this common tropical lake type. For example, we observed a significant nonlinear increase (R²_adj = 0.23, e.d.f. = 7, p<0.0001) in thermal stability over the past 20 years. This resulted in the expansion of anoxic waters and consequent deterioration of fish habitat and appears to have abated primary production; processes that may impair ecosystem services for a vulnerable human population. This study on a system representative of small tropical crater lakes highlights the far-reaching effects of global climatic change on tropical waters. Increased research efforts into tropical aquatic ecosystem health and the development of sound management practices are necessary in order to strengthen adaptive capabilities in tropical regions.     

Characterization of the major histocompatibility complex locus association with Beh?et’s disease in Iran

IntroductionThe aim of this study was to characterize the association of human leukocyte antigen (HLA) B alleles and major histocompatibility complex (MHC) single nucleotide polymorphisms (SNPs) with Behçet’s disease (BD) in an Iranian dataset.MethodsThe association of three SNPs in the MHC region previously identified as the most associated in high-density genotyping studies was tested in a case–control study on 973 BD patients and 825 controls from Iran, and the association of HLA-B alleles was tested in a subset of 681 patients and 414 controls.ResultsWe found that HLA-B*51 (P = 4.11 × 10⁻⁴¹, OR [95% CI] = 4.63[3.66-5.85]) and B*15 confer risk for BD (P = 2.83 × 10⁻², OR [95% CI] = 1.75[1.08-2.84]) in Iranian, and in B*51 negative individuals, only the B*15 allele is significantly associated with BD (P = 2.51 × 10⁻³, OR [95% CI] = 2.40[1.37-4.20]). rs76546355, formerly known as rs116799036, located between HLA-B and MICA (MHC class I polypeptide-related sequence A), demonstrated the same level of association with BD as HLA-B*51 (P_adj = 1.78 × 10⁻⁴⁶, OR [95% CI] = 5.46[4.21-7.09], and P_adj = 8.34 × 10⁻⁴⁸, OR [95% CI] = 5.44[4.20-7.05], respectively) in the HLA-B allelotyped subset, while rs2848713 was less associated (P_adj = 7.14 × 10⁻³⁵, OR [95% CI] = 3.73[2.97-4.69]) and rs9260997 was not associated (P_adj = 1.00 × 10⁻¹). Additionally, we found that B*51 genotype-phenotype correlations do not survive Bonferroni correction, while carriers of the rs76546355 risk allele predominate in BD cases with genital ulcers, positive pathergy test and positive BD family history (2.31 × 10⁻⁴ ≤ P ≤ 1.59 × 10⁻³).ConclusionsWe found that the HLA-B*51 allele and the rs76546355/rs116799036 MHC SNP are independent genetic risk factors for BD in Iranian, and that positivity for the rs76546355/rs116799036 risk allele, but not for B*51, does correlate with specific demographic characteristics or clinical manifestations in BD patients.

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Isometric scaling of above- and below-ground biomass at the individual and community levels in the understorey of a sub-tropical forest

Background and Aims Empirical studies and allometric partitioning (AP) theory indicate that plant above-ground biomass (M_A) scales, on average, one-to-one (isometrically) with below-ground biomass (M_R) at the level of individual trees and at the level of entire forest communities. However, the ability of the AP theory to predict the biomass allocation patterns of understorey plants has not been established because most previous empirical tests have focused on canopy tree species or very large shrubs.Methods In order to test the AP theory further, 1586 understorey sub-tropical forest plants from 30 sites in south-east China were harvested and examined. The numerical values of the scaling exponents and normalization constants (i.e. slopes and y-intercepts, respectively) of log–log linear M_A vs. M_R relationships were determined for all individual plants, for each site, across the entire data set, and for data sorted into a total of 19 sub-sets of forest types and successional stages. Similar comparisons of M_A/M_R were also made.Key Results The data revealed that the mean M_A/M_R of understorey plants was 2·44 and 1·57 across all 1586 plants and for all communities, respectively, and M_A scaled nearly isometrically with respect to M_R, with scaling exponents of 1·01 for all individual plants and 0·99 for all communities. The scaling exponents did not differ significantly among different forest types or successional stages, but the normalization constants did, and were positively correlated with M_A/M_R and negatively correlated with scaling exponents across all 1586 plants.Conclusions The results support the AP theory’s prediction that M_A scales nearly one-to-one with M_R (i.e. M_A ∝ M_R ^≈1·0) and that plant biomass partitioning for individual plants and at the community level share a strikingly similar pattern, at least for the understorey plants examined in this study. Furthermore, variation in environmental conditions appears to affect the numerical values of normalization constants, but not the scaling exponents of the M_A vs. M_R relationship. This feature of the results suggests that plant size is the primary driver of the M_A vs. M_R biomass allocation pattern for understorey plants in sub-tropical forests.     

Soil TPH Concentration Estimation Using Vegetation Indices in an Oil Polluted Area of Eastern China

Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m⁻² to 5.3 g m⁻² with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg⁻¹ to 652 mg kg⁻¹. The modified chlorophyll absorption ratio index (MCARI) best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R ² = 0.73) and accuracy of prediction (RMSE = 104.2 mg kg⁻¹). For other vegetation indices and red edge parameters, the R² and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg⁻¹ to 106.8 mg kg⁻¹ respectively. The traditional broadband normalized difference vegetation index (NDVI), one of the broadband multispectral vegetation indices (BMVIs), produced a prediction (R ² = 0.70 and RMSE = 110.1 mg kg⁻¹) similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable.     

表征亚热带常绿林光合作用季节变化特征的多种植被指数

利用遥感方法可以在区域尺度反演地表植被的光合生理状况和生产力变化,但亚热带常绿林冠层结构季节变化较小,传统的光谱植被指数对植被光合作用难以准确捕捉。利用2014—2015年中国科学院广东省鼎湖山森林生态试验站多角度自动光谱观测系统的光谱反射数据,分别反演传统冠层结构型植被指数(NDVI)、光合生理生化型植被指数(CCI)和叶绿素荧光型植被指数(NDFI_(685)和NDFI_(760)),并利用不同类型植被指数的组合,构建多元线性回归模型。结果表明:亚热带常绿针阔混交林三种类型植被指数均与GPP的动态变化有显著的相关性,其中,NDVI是表征GPP较优的植被指数(R~2=0.60,P0.01),其次为CCI(R~2=0.55,P0.01),而NDFI能够作为辅助指数,有效提高NDVI(R~2=0.68,P0.001)和CCI(R~2=0.67,P0.001)表征GPP的程度。多个植被指数参与构建的多元回归模型能够有效提高亚热带地区常绿林GPP季节动态变化的拟合精度,提升遥感精确评估亚热带森林生产力的能力。     

Deciphering role of technical bioprocess parameters for bioethanol production using microalgae

Microalgae biomass is considered an important feedstock for biofuels and other bioactive compounds due to its faster growth rate, high biomass production and high biomolecules accumulation over first and second-generation feedstock. This research aimed to maximize the specific growth rate of fresh water green microalgae Closteriopsis acicularis, a member of family Chlorellaceae under the effect of pH and phosphate concentration to attain enhanced biomass productivity. This study investigates the individual and cumulative effect of phosphate concentration and pH on specific growth characteristics of Closteriopsis acicularis in autotrophic mode of cultivation for bioethanol production. Central-Composite Design (CCD) strategy and Response Surface Methodology (RSM) was used for the optimization of microalga growth and ethanol production under laboratory conditions. The results showed that high specific growth rate and biomass productivity of 0.342 day⁻¹ and 0.497 g L⁻¹ day⁻¹ respectively, were achieved at high concentration of phosphate (0.115 g L⁻¹) and pH (9) at 21st day of cultivation. The elemental composition of optimized biomass has shown enhanced elemental accumulation of certain macro (C, O, P) and micronutrients (Na, Mg, Al, K, Ca and Fe) except for nitrogen and sulfur. The Fourier transform infrared spectroscopic analysis has revealed spectral peaks and high absorbance in spectral range of carbohydrates, lipids and proteins, in optimized biomass. The carbohydrates content of optimized biomass was observed as 58%, with 29.3 g L⁻¹ of fermentable sugars after acid catalyzed saccharification. The bioethanol yield was estimated as 51 % g ethanol/g glucose with maximum of 14.9 g/L of bioethanol production. In conclusion, it can be inferred that high specific growth rate and biomass productivity can be achieved by varying levels of phosphate concentration and pH during cultivation of Closteriopsis acicularis for improved yield of microbial growth, biomass and bioethanol production.     

Biomass and primary production of a 8–11 m depth meadow versus <3 m depth meadows of the seagrass Cymodocea nodosa (Ucria) Ascherson

Current knowledge about the abundance, growth, and primary production of the seagrass Cymodocea nodosa (Ucria) Ascherson is biased towards shallow (depth <3 m) meadows although this species also forms extensive meadows at larger depths along the coastlines. The biomass and primary production of a C. nodosa meadow located at a depth of 8–11 m was estimated at the time of maximum annual vegetative development (summer) using reconstruction techniques, and compared with those available from shallow meadows of this species. A depth-referenced data base of values at the time of maximum annual development was compiled to that end. The vegetative development of C. nodosa at 8–11 m depth was not different from that achieved by shallow (depth <3 m) meadows of this species. Only shoot density, which decreased from 1637 to 605 shoots m⁻², and the annual rate of elongation of the horizontal rhizome, which increased from 23 to 71 cm apex⁻¹ year⁻¹, were different as depth increased from <3 to 8–11 m. Depth was a poor predictor of the vegetative development and primary production of C. nodosa. The biomass of rhizomes and roots decreased with depth (g DW m⁻² = 480 (±53, S.E.) − 32 (±15, S.E.) depth (in m); R² = 0.12, F = 4.65, d.f. = 35, P = 0.0381) which made total biomass of the meadow to show a trend of decrease with depth but the variance of biomass data explained by depth was low. The annual rate of elongation of the horizontal rhizome showed a significant positive relationship with depth (cm apex⁻¹ year⁻¹ = 18 (±5.1, S.E.) + 5.0 (±1.33, S.E.) depth (in m); R² = 0.50, F = 14.07, d.f. = 14, P = 0.0021). As shoot size and growth did not change significantly with depth, the reduction of shoot density should drive any changes of biomass and productivity of C. nodosa as depth increases. The processes by which this reduction of C. nodosa abundance with depth occur remain to be elucidated.