Development of a macrophyte-based index of biotic integrity for Minnesota lakes

Traditional approaches for managing aquatic resources have often failed to account for effects of anthropogenic disturbances on biota that are not directly reflected by chemical and physical proxies of environmental condition. The index of biotic integrity (IBI) is a potentially effective assessment method to integrate ecological, functional, and structural aspects of aquatic systems. A macrophyte-based IBI was developed for Minnesota lakes to assess the ability of aquatic plant communities to indicate environmental condition. The index was developed using quantitative point intercept vegetation surveys for 97 lakes that represent a range of limnological and watershed characteristics. We followed an approach similar to that used in Wisconsin to develop the aquatic macrophyte community index (AMCI). Regional adaptation of the AMCI required the identification of species representative of macrophyte communities in Minnesota. Metrics and scaling methods were also substantially modified to produce a more empirically robust index. Regression analyses indicated that IBI scores reflected statewide differences in lake trophic state (R² = 0.57, F = 130.3, df = 1, 95, p < 0.005), agricultural (R² = 0.51, F = 83.0, df = 1, 79, p < 0.005), urban (R² = 0.22, F = 23.0, df = 1, 79, p < 0.005), and forested land uses (R² = 0.51, F = 84.7, df = 1, 79, p < 0.005), and county population density (R² = 0.14, F = 16.6, df = 1, 95, p < 0.005). Variance partitioning analyses using multiple regression models indicated a unique response of the IBI to human-induced stress separate from a response to natural lake characteristics. The IBI was minimally affected by differences in sample point density as indicated by Monte Carlo analyses of reduced sampling effort. Our analysis indicates that a macrophyte IBI calibrated for Minnesota lakes could be useful for identifying differences in environmental condition attributed to human-induced stress gradients.     

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.     

Evaluating the performance of multiple remote sensing indices to predict the spatial variability of ecosystem structure and functioning in Patagonian steppes

Assessing the spatial variability of ecosystem structure and functioning is an important step towards developing monitoring systems to detect changes in ecosystem attributes that could be linked to desertification processes in drylands. Methods based on ground-collected soil and plant indicators are being increasingly used for this aim, but they have limitations regarding the extent of the area that can be measured using them. Approaches based on remote sensing data can successfully assess large areas, but it is largely unknown how the different indices that can be derived from such data relate to ground-based indicators of ecosystem health. We tested whether we can predict ecosystem structure and functioning, as measured with a field methodology based on indicators of ecosystem functioning (the landscape function analysis, LFA), over a large area using spectral vegetation indices (VIs), and evaluated which VIs are the best predictors of these ecosystem attributes. For doing this, we assessed the relationship between vegetation attributes (cover and species richness), LFA indices (stability, infiltration and nutrient cycling) and nine VIs obtained from satellite images of the MODIS sensor in 194 sites located across the Patagonian steppe. We found that NDVI was the VI best predictor of ecosystem attributes. This VI showed a significant positive linear relationship with both vegetation basal cover (R² = 0.39) and plant species richness (R² = 0.31). NDVI was also significantly and linearly related to the infiltration and nutrient cycling indices (R² = 0.36 and 0.49, respectively), but the relationship with the stability index was weak (R² = 0.13). Our results indicate that VIs obtained from MODIS, and NDVI in particular, are a suitable tool for estimate the spatial variability of functional and structural ecosystem attributes in the Patagonian steppe at the regional scale.     

Mapping riparian condition indicators in a sub-tropical savanna environment from discrete return LiDAR data using object-based image analysis

Mapping, monitoring and managing the environmental condition of riparian zones are major focus areas for local and state governments in Australia. New remotely sensed data techniques that can provide the required mapping accuracies, complete spatial coverage and processing and mapping transferability are currently being developed for use over large spatial extents. The research objective was to develop and apply an approach for mapping riparian condition indicators using object-based image analysis of airborne Light Detection and Ranging (LiDAR) data. The indicators assessed were: streambed width; riparian zone width; plant projective cover (PPC); longitudinal continuity; coverage of large trees; vegetation overhang; and stream bank stability. LiDAR data were captured on 15 July 2007 for two 5 km stretches along Mimosa Creek in Central Queensland, Australia. Field measurements of riparian vegetation structural and landform parameters were obtained between 28 May and 5 June 2007. Object-based approaches were developed for mapping each riparian condition indicator from the LiDAR data. The validation and empirical modelling results showed that the object-based approach could be used to accurately map the riparian condition indicators (R² = 0.99 for streambed width, R² = 0.82 for riparian zone width, R² = 0.89 for PPC, R² = 0.40 for bank stability). These research findings will be used in a 26,000 km mapping project assessing riparian vegetation and physical form indicators from LiDAR data in Victoria, Australia.     

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.     

Trispyrazolylmethane piano stool complexes of iron(II) and cobalt(II)

A series of cationic trispyrazolylmethane complexes of the general form [Tm^RM(CH₃CN)₃]²⁺ (Tm = tris(pyrazolyl)methane, 1, R = 3,5-Me₂, M = Fe(II); 2, R = 3-Ph, M = Fe(II); 3, R = 3,5-Me₂, M = Co(II); 4, R = 3-Ph, M = Co(II)) with ‘piano-stool’ structures was prepared by the reaction of the N₃tripodal ligands (Tm^R)with [(CH₃CN)₆M](BF₄)₂ in a 1:1 stoichiometric ratio. Magnetic susceptibility measurements indicate that all four complexes with BF₄⁻ counter anions are paramagnetic, high-spin systems in the solid state with μ_eff at high temperatures of 5.2 (1, S = 2), 5.4 (2, S = 2), 4.9 (3, S = 3/2) and 4.6 (4, S = 3/2) BM, respectively. Comparisons of bond lengths from the metal centre to the Tm^R nitrogen donors, and from the metal centre to the acetonitrile nitrogen donors indicate that the neutral tripodal ligands appear to be more weakly coordinated to the metal centre than are the acetonitrile ligands. Reactions of these tripodal complexes with bidentate phosphine ligands, such as 1,2-diphosphinoethane or 1,2-bis(diallylphosphino)ethane leads to displacement of the tripodal ligand, or to the formation of more thermally stable bis-ligand complexes M(Tm^R)₂ (R = 3,5-dimethyl).     

Predominance of terrestrial organic matter in sediments from a cyanobacteria- blooming hypereutrophic lake

Although an understanding of the quantity and quality of sedimentary organic matter (SOM) pools is necessary to design sound environmental management strategies for lacustrine systems, the characterization of organic matter sources and the assessment of their relative contributions to eutrophic and inland lake sediments remain insufficient. In this study, the contribution of potential organic matter sources to sediments in shallow and hypereutrophic lake Taihu, China was assessed on the molecular level using source-specific fatty acid biomarkers. The results indicated that SOM was composed mainly of terrestrial plants with a maximal contribution of 45.3 ± 2.4% to the total organic carbon, which accounted for approximately 66% among the determined organic matter sources. Evidence suggests the terrestrial plants remained in a fresh state in surface sediments: the correlation (R² = 0.62, p < 0.05) between bacterial and terrestrial plant carbon was strong. On the other hand, aquatic plant and bacterial carbon contributed 5–15% to the total organic carbon, which was followed by the faint contribution (<5% of total organic carbon) of algae-derived organic carbon including cyanobacteria, diatoms, and dinoflagellates. The results provided details of the contributions of SOM sources, illustrating the usefulness of fatty acid biomarkers in discriminating organic matter sources within lake environments. Although organic matter sources of sediments varied in spatial and temporal patterns, the strong correlation between terrestrial plant and total organic carbon (R² = 0.60, p < 0.05) indicates that terrestrial plants were the dominant source in lake sediments.     

Methyl-palladium(II) complexes of pyridine-bridged bis(nucleophilic heterocyclic carbene) ligands: Substituent effects on structure,stability, and catalytic performance

A series of discrete, mononuclear palladium(II)–methyl complexes, together with several palladium(II)–chloro analogues, of pyridine-functionalised bis-NHC ligands have been prepared via ligand transmetallation from the silver(I)-NHC complexes. The reported complexes comprise examples with both the methylene-bridged 2,6-bis[(3-R-imidazolin-2-yliden-1-yl)methyl]pyridine (_RC^∧N^∧C; R = Mes, dipp, ^tBu) and planar 2,6-bis(3-R-imidazolin-2-yliden-1-yl)pyridine (_RCNC; R = Mes, dipp) ligands and, when combined with the previously reported _MeC^∧N^∧C/_MeCNC examples, cover a broad spectrum of ligand substituent steric and electronic properties, including the bulky Mes and dipp groups frequently used in catalytic applications. The palladium(II) complexes have been characterised by a variety of methods, including single crystal X-ray crystallography, with the shielding of the Pd–Me groups in the proton NMR spectra of some of the N-aryl substituted examples correlated with the proximity of the aryl rings to the methyl group in the solid state structures. The [PdMe(_RC^∧N^∧C/_RCNC)]⁺ complexes undergo thermal degradation via reductive methyl-NHC coupling to give 2-methyl-3-R-imidazolium-1-yl species with relative stabilities in the order of [PdMe(_MesC^∧N^∧C)]BF₄ > [PdMe(_MeC^∧N^∧C)]BF₄ ≈ [PdMe(_MesCNC)]BF₄ > [PdMe(_MeCNC)]BF₄ > [PdMe(_tBuC^∧N^∧C)]BF₄ ≫ [PdMe(_tBuCNC)]BF₄ (not isolable). A comparison of the activity of the complexes as precatalysts in a model Heck coupling reaction shows greatest activity in those species bearing bulkier N-substituents, with complexes bearing _RC^∧N^∧C ligands generally more efficient precatalysts than those bearing _RCNC ligands.     

Unusual hepatic mitochondrial arginase in an Indian air-breathing teleost,Heteropneustes fossilis: Purification and characterization

A functional urea cycle with both cytosolic (ARG I) and mitochondrial (ARG II) arginase activity is present in the liver of an ureogenic air-breathing teleost, Heteropneustes fossilis. Antibodies against mammalian ARG II showed no cross-reactivity with the H. fossilis ARG II. ARG II was purified to homogeneity from H. fossilis liver. Purified ARG II showed a native molecular mass of 96 kDa. SDS–PAGE showed a major band at 48 kDa. The native enzyme, therefore, appears to be a homodimer. The pI value of the enzyme was 7.5. The purified enzyme showed maximum activity at pH 10.5 and 55 °C. The K_m of purified ARG II for l-arginine was 5.25 ± 1.12 mM. l-Ornithine and N^ω-hydroxy-l-arginine showed mixed inhibition with K_i values 2.16 ± 0.08 and 0.02 ± 0.004 mM respectively. Mn^+ 2 and Co^+ 2 were effective activators of arginase activity. Antibody raised against purified H. fossilis ARG II did not cross-react with fish ARG I, and mammalian ARG I and ARG II. Western blot with the antibodies against purified H. fossilis hepatic ARG II showed cross reactivity with a 96 kDa band on native PAGE and a 48 kDa band on SDS–PAGE. The molecular, immunological and kinetic properties suggest uniqueness of the hepatic mitochondrial ARG II in H. fossilis.     

Climatic dependency of soil organic carbon isotopic composition along the S–N Transect from 34°N to 52°N in central-east Asia

We explored the relationships between surface-soil (1–20 cm) organic carbon isotopic signatures and associated climatic factors in central-east Asia in an attempt to develop transfer functions that can be used to retrieve the paleoclimatic information stored in the thick eolian–paleosol sequences within the area. Our analysis shows that the negative correlation between the surface-soil organic δ¹³C values and the mean annual precipitation is robust (R² = 0.453; n = 196; p < 0.05) and the negative correlation with the growing-season (April–September) precipitation is more significant (R² = 0.4966; n = 196; p < 0.05). Our study further shows that the positive correlation between the surface-soil organic δ¹³C values and mean growing-season aridity is most significant (R² = 0.5805; n = 196; p < 0.05). We have smoothed both the organic δ¹³C values and the mean growing-season aridity values using a 3-point moving-window average-filter method in an attempt to remove some of random errors and found that the positive correlation between the two is further increased (R² =  0.7784; n =  192; p < 0.05). These robust linear relationships demonstrate their value in reconstructing paleoclimate changes in the study area. The documented climatic dependency of the surface-soil carbon isotopic composition in the study area might have resulted both from the humidity-related isotopic enrichment processes of the dominant C₃ plants (stomatal conductance and photosynthetic discrimination) and from the aridity-related abundance of C₄ plants (mainly Chenopodiaceae species) along the S–N bioclimatic gradient.     

Comparison of two type IV hyperthermophilic adenylyl cyclases characterizations from the archaeon Pyrococcus furiosus

In this paper, two genes that encoded two soluble type IV adenylyl cyclases (AC) from the hyperthermophilic archaeon Pyrococcus furiosus (PFAC I and PFAC II) were cloned and expressed in Escherichia coli (E. coli) BL21 (DE3). Amino acid sequence analysis of the two enzymes showed 29% homology. PFAC I and PFAC II were both Mn²⁺ activated enzyme. They were purified by His-trap chromatography and had a specific activity of 3.1 × 10³ U/mg at pH 10.0, 95 °C (PFAC I) and 2.0 × 10³ U/mg at pH 11.0, 95 °C (PFAC II), respectively. The K_m and k_cat of PFAC I was 1.38 mM and 1.11 s⁻¹. The K_m and k_cat of PFAC II was 1.44 mM and 0.80 s⁻¹. The thermostability of PFAC I and PFAC II were higher than the soluble type IV adenylyl cyclases from Yersinia pestis (YpAC-IV). All of the properties suggested that these two adenylyl cyclases may be useful for the industrial producing of cyclic adenosine 3′,5′-monophosphate (cAMP).     

Comparative regional-scale soil salinity assessment with near-ground apparent electrical conductivity and remote sensing canopy reflectance

Soil salinity is recognized worldwide as a major threat to agriculture, particularly in arid and semi-arid regions. Producers and decision makers need updated and accurate maps of salinity in agronomically and environmentally relevant ranges (i.e., <20 dS m⁻¹, when salinity is measured as electrical conductivity of the saturation extract, EC_e). State-of-the-art approaches for creating accurate EC_e maps beyond field scale (i.e., 1 km²) include: (i) Analysis Of Covariance (ANOCOVA) of near-ground measurements of apparent soil electrical conductivity (EC_a) and (ii) regression modeling of multi-year remote sensing canopy reflectance and other co-variates (e.g., crop type, annual rainfall). This study presents a comparison of the two approaches to establish their viability and utility. The approaches were tested using 22 fields (total 542 ha) located in California’s western San Joaquin Valley. In 2013 EC_a-directed soil sampling resulted in the collection of 267 soil samples across the 22 fields, which were analyzed for EC_e, ranging from 0 to 38.6 dS m⁻¹. The ANOCOVA EC_a-EC_e model returned a coefficient of determination (R²) of 0.87 and root mean square prediction error (RMSPE) of 3.05 dS m⁻¹. For the remote sensing approach seven years (2007–2013) of Landsat 7 reflectance were considered. The remote sensing salinity model had R² = 0.73 and RMSPE = 3.63 dS m⁻¹. The robustness of the models was tested with a leave-one-field-out (lofo) cross-validation to assure maximum independence between training and validation datasets. For the ANOCOVA model, lofo cross-validation provided a range of scenarios in terms of RMSPE. The worst, median, and best fit scenarios provided global cross-validation R² of 0.52, 0.80, and 0.81, respectively. The lofo cross-validation for the remote sensing approach returned a R² of 0.65. The ANOCOVA approach performs particularly well at EC_e values <10 dS m⁻¹, but requires extensive field work. Field work is reduced considerably with the remote sensing approach, but due to the larger errors at low EC_e values, the methodology is less suitable for crop selection, and other practices that require accurate knowledge of salinity variation within a field, making it more useful for assessing trends in salinity across a regional scale. The two models proved to be viable solutions at large spatial scales, with the ANOCOVA approach more appropriate for multiple-field to landscape scales (1–10 km²) and the remote sensing approach best for landscape to regional scales (>10 km²).     

Tetracycline-resistant bacteria as indicators of antimicrobial resistance in protected waters—The example of the Drwęca River Nature Reserve (Poland)

The objective of this study was to determine the suitability of Tet^R tetracycline-resistant bacteria as potential indicators of drug resistance, a parameter of the microbiological quality of river waters in natural reserves which are threatened by man-made pollution. The microbiological assays covered a 15-km long section of the upper reach of the Drw?ca River (Poland), a part of the European Ecological “Natura 2000” Network of nature protected areas. The quality of the investigated ecosystem was affected by surface runoffs from the river's agricultural catchment as well as outflows from three fish farms. The counts of Tet^R bacteria, incubated at 14 °C and 28 °C on TSA medium with sheep blood and tetracycline, were determined in river water samples. The highest counts of both bacterial groups were determined in samples collected from sites behind fish farms. A statistical analysis of the abundance of Tet^R14 °C and Tet^R28 °C bacteria revealed significant differences in the size of Tet^R28 °C populations at the studied sampling sites (p = 0.0011), which is why hemolytic bacteria of this group (HemTet^R28 °C) were selected for further investigations. The predominant strains in the group of 86 HemTet^R28 °C isolates obtained by 16S rRNA gene sequencing were Pseudomonas fluorescens (42 isolates) and Aeromonas hydrophila (28 isolates). Analyses of the identified HemTet^R28 °C strains demonstrated MIC ≥256 μg/ml in more than 50% isolates. The MAR index of HemTet^R28 °C was in the range of 0.67 at the control site to 1 at sites behind fish farms. The results suggest that tetracycline-resistant bacteria, in particular HemTet^R28 °C, are a reliable indicator of antimicrobial resistance and the microbial quality of surface waters polluted due to human activity. The above can be attributed to several factors: (I) the highest percentage share of HemTet^R28 °C among HPC28 °C was noted at sites behind fish farms, (II) tetracycline-resistant bacteria quickly respond to environmental changes, as demonstrated by the high level of resistance to tetracycline and a very high MAR index, and (III) genera/species that are easy to culture under laboratory conditions dominate in the qualitative and quantitative composition of the studied bacteria.     

Prediction of Egeria najas and Egeria densa occurrence in a large subtropical reservoir (Itaipu Reservoir,Brazil-Paraguay)

Incidence data of two native submerged aquatic macrophytes (Egeria najas Planch. and Egeria densa Planch.) were obtained in eight arms of a large (1350 km²) subtropical reservoir (Itaipu Binacional Reservoir, Brazil-Paraguay). Environmental variables were measured simultaneously. Two large-scale surveys in the same localities identified by a global positioning system were carried out in April 1999 (n = 235) and January 2001 (n = 230). Logistic regressions were used to test the effect of environmental variables on the likelihood of E. najas and E. densa presence or absence. The two species were found under different environmental conditions: conductivity, light attenuation coefficient (k) and fetch were, in this order, the most important environmental variables in predicting the probability of occurrence of E. najas, whereas light attenuation coefficient was the main predictor of the probability of occurrence of E. densa. Thus, both species were negatively affected by the light attenuation coefficient. However, this effect was stronger in E. densa. The small area occupied by these species may be accounted for by the permanent high turbidity of Itaipu Reservoir. Additionally, the dominance of E. najas over of E. densa can be explained by the probably higher light requirements of E. densa. In other reservoirs worldwide, with higher water transparency, the opposite is frequently true. Between 1999 and 2001, an episodic water-level drawdown (5 m) caused the disappearance of submerged vegetation. After water-level normalization, previous vegetation presence (in 1999) was an important predictor of the probability of occurrence of E. najas in 2001.     

Biomorphometric characteristics of different types of sensilla detected on the antenna of Helicoverpa armigera by scanning electron microscopy

A morphometric study on H. armigera antenna showed four styles of sensilla, i.e., styloconica, chaetica, coeloconica, and trichodea, and their numbers were estimated. Sensilla trichodea detect inter and intraspecific communication signals and was the most numerous. They were divided into three types: type I, the longest, with a length of 34.04 ± 3.16 μm and about 2.16 to 2.42 μm in diameter at its base; 2) type II, intermediate, with a length of 22.58 ± 0.77 μm and basal diameter of 1.8–2.52 μm; 3) type III, the shortest sensilla trichodea, with a length of 7.62 ± 0.4 μm and a range in diameter similar to that of type II. The length of the female sensilla trichodea was longer than that of the male. The total number of sensilla trichodea was estimated to be 7520 on the antenna of the female, and 6831 on the male antenna. The lengths of the sensilla trichodea type I and type III were significantly different on male (t = 4.6881, P = 0.0034) and female antenna (t = 18.9852, P = 0.0001). An estimation of the predicted surface area of the most numerous type I on sampled segments between the 12th and 20th segments from a female of H. armigera showed a surface area of 5 × 10³ μm² and a sensillar density of 38 sensilla/10³ μm². The fraction of sensilla-occupied surface area was 0.4 μm².     

Emergy and exergy evaluation of a dike-pond project in the drawdown zone (DDZ) of the Three Gorges Reservoir (TGR)

The dike-pond system was a form of ecological engineering that was a component of successional dikes and ponds along the banks of the Pengxi River in the drawdown zone (DDZ) of the Three Gorges Reservoir (TGR). The application of science-based evaluation system was appropriate for the flows of emergy in this agricultural ecosystem. The Emergy Analysis (EmA) has the ability to transform different types of inputs to a common form to allow meaningful comparisons across different systems. This study made use of the emergy analysis that assessed two different types of farming methods in the DDZ of the TGR. One method was planning crops in a dike-pond system (model I), and the other method was conventional agriculture (model II). In addition, the Exergies of both yields of agriculture methods were calculated, and the Exergy and Emergy Density (ED) were combined to explore the quality of these methods. The results showed that the two models relied on different resources. The ED yield of both models were similar, but the emergy investment of model II was greater than that of model I. Model II also used less renewable energy input to the agricultural systems than model I. The agricultural emergy sustainability index (AESI) of model I system (AESI = 2.4 > 1) was greater than that of model II system (AESI = 0.5 < 1), which indicated that the sustainable development of model I was stronger than that of model II in the DDZ of the TGR. The ratio Exergy/Emergy density (R_ex/em) in the two models of different agricultural system were 121.52 × 10⁻³ J/sej (Model I) and 24.19 × 10⁻³ J/sej (model II). Model I was greater than model II, and the result intimated that the model I agricultural system was a new method in the DDZ, but it was older and closer to the steady state than model II. The Emergy and Exergy analysis certifies that model I has a more acceptable and more sustainable development potential and is more stabilized in the DDZ of the TGR.     

Altitude modifies species richness–nutrient indicator value relationships in a country-wide survey of grassland vegetation

Nutrient enrichment is a threat to botanical diversity in Europe, and its assessment is part of biodiversity monitoring schemes. In Switzerland, this is done by calculating the average nutrient (N) indicator value of the vegetation based on a country-wide systematic vegetation survey. However, it is questionable whether N values indicate eutrophication and resulting species loss equally well across an entire country, which includes wide topographic gradients and distinct biogeographic regions. Here we analyze vascular plant species lists from 415 grassland plots (10 m²) between 365 and 2770 m a.s.l. throughout Switzerland to investigate how the relationship between N value and species richness differs with altitude and among regions. The N value strongly decreased with altitude (piecewise regression: r² = 0.77), particularly between 800 and 2000 m a.s.l., where this decrease was related to a decreasing proportion of fertilized grasslands. In the alpine belt, lower N values were associated with a greater frequency of acidic soils and a restricted species pool. Vascular plant species richness was maximal at intermediate altitude (piecewise regression: r² = 0.33) and intermediate N value (polynomial regression: r² = 0.46). When analyzed separately by altitudinal belt, the relationship between species richness and N value was negative in the lowlands and montane belt but unimodal in the subalpine belt. In the alpine belt, soil pH (R indicator values) explained most of the variation in species richness. Two indices of between-plot diversity (floristic dissimilarity and the contribution of individual plots to total species richness) were negatively related to N values from the lowlands to the subalpine belt but not in the alpine belt. All relationships differed little among the biogeographic regions of Switzerland, but they might be modified by changes in management and by the expansion of common lowland species into mountain grasslands.     

Whole crop rice silage: Predictions of yield and content of metabolizable energy,metabolizable protein and other nutrients for dairy cows from crop maturity and botanical fractions at harvest

The study investigated the suitability of stage of maturity and botanical fractions of whole crop rice (WCR) to predict yield and nutritive value of ensiled WCR for dairy cows. Eight varieties of WCR (i.e., Akichikara, Fukuhibiki, Habataki, Hamasari, Hokuriku 168, Kusanami, Tamakei 96, Yumetoiro) were harvested at four stages of maturity (i.e., 10, 22, 34, 45 days after flowering [DAF]) and ensiled. Dry matter (DM) yield at each harvest was determined. Silage samples were fractionated into four botanical fractions being: leaf blade, leaf sheath, stem and head. Silage samples were also analyzed for chemical composition, fermentation characteristics, in situ DM and N disappearance. Metabolizable energy (ME) and metabolizable protein (MP) content of samples were estimated according to Terada et al. (1988) and AFRC (1993), respectively. Relationships between maturity or proportions of botanical fractions and contents of WCR silage in terms of DM, ME and MP, and their yields, were estimated by correlation and regression analysis. Stage of maturity was positively related (P<0.001) to ME content (R² = 0.46; y = 4.53 + 0.08X) and MP content (R² = 0.56; y = 22.26 + 0.76X), and DM yield (R² = 0.63; y = 9.21 + 0.12X), ME yield (R² = 0.68, y = 36931 + 1708X) and MP yield (R² = 0.72, y = 161.0 + 14.15X) of WCR. Proportion of leaf was negatively related to yields and nutritive value of ensiled WCR, whilst proportion of head was positively related (P<0.05 to <0.001). Proportion of head was best related to the ME content (R² = 0.72; y = 3.26 + 0.009X), MP content (R² = 0.72; y = 12.31 + 0.079X), and DM yield (R² = 0.41; y = 9.02 + 0.009X), ME yield (R² = 0.76, y = 19494 + 165.5X), and MP yield (R² = 0.75, y = 34.37 + 1.32X) of WCR. Results suggest that to optimize yield and nutritive value, WCR should be ensiled within 40 DAF and the proportion of head should be equal to or more than 500 g per kg DM of WCR silage. Stage of maturity and proportion of head of WCR predict yields of DM, ME and MP of WCR, and their contents, in WCR silage with acceptable accuracy. However, these relationships need to be validated using large data sets and in vivo studies.     

Synthesis and anti-acetylcholinesterase properties of novel β- and γ-substituted alkoxy organophosphonates

Activated organophosphate (OP) insecticides and chemical agents inhibit acetylcholinesterase (AChE) to form OP-AChE adducts. Whereas the structure of the OP correlates with the rate of inhibition, the structure of the OP-AChE adduct influences the rate at which post-inhibitory reactivation or aging phenomena occurs. In this report, we prepared a panel of β-substituted ethoxy and γ-substituted propoxy phosphonoesters of the type p-NO₂PhO-P(X)(R)[(O(CH₂)_nZ] (R = Me, Et; X = O, S; n = 2, 3; Z = halogen, OTs) and examined the inhibition of three AChEs by select structures in the panel. The β-fluoroethoxy methylphosphonate analog (R = Me, Z = F, n = 2) was the most potent anti-AChE compound comparable (k_i ～6 × 10⁶ M^?1 min^?1) to paraoxon against EEAChE. Analogs with Z = Br, I, or OTs were weak inhibitors of the AChEs, and methyl phosphonates (R = Me) were more potent than the corresponding ethyl phosphonates (R = Et). As expected, analogs with a thionate linkage (PS) were poor inhibitors of the AChEs.     

Airborne hyperspectral data predict Ellenberg indicator values for nutrient and moisture availability in dry grazed grasslands within a local agricultural landscape

Species-based ecological indices, such as Ellenberg indicators, reflect plant habitat preferences and can be used to describe local environment conditions. One disadvantage of using vegetation data as a substitute for environmental data is the fact that extensive floristic sampling can usually only be carried out at a plot scale within limited geographical areas. Remotely sensed data have the potential to provide information on fine-scale vegetation properties over large areas. In the present study, we examine whether airborne hyperspectral remote sensing can be used to predict Ellenberg nutrient (N) and moisture (M) values in plots in dry grazed grasslands within a local agricultural landscape in southern Sweden. We compare the prediction accuracy of three categories of model: (I) models based on predefined vegetation indices (VIs), (II) models based on waveband-selected VIs, and (III) models based on the full set of hyperspectral wavebands. We also identify the optimal combination of wavebands for the prediction of Ellenberg values. The floristic composition of 104 (4 m × 4 m grassland) plots on the Baltic island of Öland was surveyed in the field, and the vascular plant species recorded in the plots were assigned Ellenberg indicator values for N and M. A community-weighted mean value was calculated for N (mN) and M (mM) within each plot. Hyperspectral data were extracted from an 8 m × 8 m pixel window centred on each plot. The relationship between field-observed and predicted mean Ellenberg values was significant for all three categories of prediction models. The performance of the category II and III models was comparable, and they gave lower prediction errors and higher R² values than the category I models for both mN and mM. Visible and near-infrared wavebands were important for the prediction of both mN and mM, and shortwave infrared wavebands were also important for the prediction of mM. We conclude that airborne hyperspectral remote sensing can detect spectral differences in vegetation between grassland plots characterised by different mean Ellenberg N and M values, and that remote sensing technology can potentially be used to survey fine-scale variation in environmental conditions within a local agricultural landscape.