Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment

A Canopy Height Profile (CHP) procedure presented in Harding et al. (2001) for large footprint LiDAR data was tested in a closed canopy environment as a way of extracting vertical foliage profiles from LiDAR raw-waveform. In this study, an adaptation of this method to small-footprint data has been shown, tested and validated in an Australian sparse canopy forest at plot- and site-level. Further, the methodology itself has been enhanced by implementing a dataset-adjusted reflectance ratio calculation according to Armston et al. (2013) in the processing chain, and tested against a fixed ratio of 0.5 estimated for the laser wavelength of 1550nm. As a by-product of the methodology, effective leaf area index (LAIe) estimates were derived and compared to hemispherical photography-derived values. To assess the influence of LiDAR aggregation area size on the estimates in a sparse canopy environment, LiDAR CHPs and LAIes were generated by aggregating waveforms to plot- and site-level footprints (plot/site-aggregated) as well as in 5m grids (grid-processed). LiDAR profiles were then compared to leaf biomass field profiles generated based on field tree measurements. The correlation between field and LiDAR profiles was very high, with a mean R2 of 0.75 at plot-level and 0.86 at site-level for 55 plots and the corresponding 11 sites. Gridding had almost no impact on the correlation between LiDAR and field profiles (only marginally improvement), nor did the dataset-adjusted reflectance ratio. However, gridding and the dataset-adjusted reflectance ratio were found to improve the correlation between raw-waveform LiDAR and hemispherical photography LAIe estimates, yielding the highest correlations of 0.61 at plot-level and of 0.83 at site-level. This proved the validity of the approach and superiority of dataset-adjusted reflectance ratio of Armston et al. (2013) over a fixed ratio of 0.5 for LAIe estimation, as well as showed the adequacy of small-footprint LiDAR data for LAIe estimation in discontinuous canopy forests.

Evaluation of cacao (Theobroma cacao L.) clones against seven Colombian isolates of Moniliophthora roreri (Cif.) Evans et al., representing four major genetic groupings of the pathogen in cacao

Artificial pod inoculation was used to compare the relative aggressiveness of seven Colombian isolates of Moniliophthora roreri (the causal agent of moniliasis or frosty pod disease), representing four major genetic groupings of the pathogen in cacao (cocoa), when applied to five diverse cacao genotypes (ICS-1, ICS-95, TSH-565, SCC-61 and CAP-34) at La Suiza Experimental Farm, Santander Department, Colombia. The following variables were evaluated 9 weeks after inoculation of 2- to 3-month-old pods with spore suspensions (1.2 x 10(5) spores mL(-1)): (i) disease incidence (DI); (ii) external severity (ES); and (iii) internal severity (IS). IS was found to be of greatest value in classifying the reaction of the host genotype against M. roreri. Genetic variation reported between isolates and cacao genotypes was not matched by similar diversity in their aggressiveness. All isolates were generally highly aggressive against most cacao genotypes, with only two isolates showing reduced IS and ES reactions. There was considerable variation between clones in the IS and ES scores, but one cultivated clone (ICS-95) displayed a significant level of resistance against all seven isolates. This clone may be useful in cacao breeding initiatives for resistance to moniliasis of cacao.

Comment on: Fruit and seed biomineralization and its effect on preservation by E. Messager et al.; in: Archaeological and Anthropological Sciences (2010) 2:25–34. DOI 10.1007/s12520-010-0024-1

This article provides a brief critique of a recent article on biomineralisation and preservation. It gives a summary of the difference between biomineralisation and mineral replacement, and addresses problems with the interpretation of FT-IR data. The lack of contextual information for the samples studied is another problem which is highlighted.

Sugar signaling in root responses to low phosphorus availability

Over the last decade, major advances have been made in our understanding of how plants sense, signal, and respond to soil phosphorus (P) availability (Amtmann et al., 2006; White and Hammond, 2008; Nilsson et al., 2010; Yang and Finnegan, 2010; Vance, 2010; George et al., 2011). Previously, we have reviewed the potential for shoot-derived carbohydrate signals to initiate acclimatory responses in roots to low P availability. In this context, these carbohydrates act as systemic plant growth regulators (Hammond and White, 2008). Photosynthate is transported primarily to sink tissues as Suc via the phloem. Under P starvation, plants accumulate sugars and starch in their leaves. Increased loading of Suc to the phloem under P starvation primarily functions to relocate carbon resources to the roots, which increases their size relative to the shoot (Hermans et al., 2006). The translocation of sugars via the phloem also has the potential to initiate sugar signaling cascades that alter the expression of genes involved plant responses to low P availability. These include optimizing root biochemistry to acquire soil P, through increased expression and activity of inorganic phosphate (Pi) transporters, the secretion of acid phosphatases and organic acids to release P from the soil, and the optimization of internal P use (Hammond and White, 2008). Here, we provide an Update to the field of plant signaling responses to low P availability and the interactions with sugar signaling components. Advances in the P signaling pathways and the roles of hormones in signaling plant responses to low P availability are also reviewed, and where possible their interactions with potential sugar signaling pathways.

Co3M2S2 (M ¼ Sn, In) shandites as tellurium-free thermoelectrics

Chemical substitution in Co3Sn2-xInxS2 (0 # x # 2) enables tuning of the Fermi level within narrow bands of Co d-states. This results in a compositionally induced double metal–semiconductor–metal transition and manipulation of the thermoelectric power factor. The maximum power factor (14 mW cm-1 K-2) is found for x ¼ 0.85, which corresponds to ZT z 0.2 at 300 K.

Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations

We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02Wm−2, with a mean of −0.27Wm−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information from the other AeroCom models reduces the range and slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35Wm−2. Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study.We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results.

A note on boundary layer friction in baroclinic cyclones

The interaction between extratropical cyclones and the underlying boundary layer has been a topic of recent discussion in papers by Adamson et al (2006) and Beare (2007). Their results emphasise different mechanisms through which the boundary layer dynamics may modify the growth of a baroclinic cyclone. By using different sea-surface temperature distributions and comparing the low-level winds, the differences are exposed and both of the proposed mechanisms appear to be acting within a single simulation.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model.

1. There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6. Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

Adaptive approximate Bayesian computation

Sequential techniques can enhance the efficiency of the approximate Bayesian computation algorithm, as in Sisson et al.'s (2007) partial rejection control version. While this method is based upon the theoretical works of Del Moral et al. (2006), the application to approximate Bayesian computation results in a bias in the approximation to the posterior. An alternative version based on genuine importance sampling arguments bypasses this difficulty, in connection with the population Monte Carlo method of Cappe et al. (2004), and it includes an automatic scaling of the forward kernel. When applied to a population genetics example, it compares favourably with two other versions of the approximate algorithm.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model

1.There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6.Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

Simulating the detailed chemical composition of secondary organic aerosol formed on a regional scale during the TORCH 2003 campaign in the southern UK

Following on from the companion study (Johnson et al., 2006), a photochemical trajectory model (PTM) has been used to simulate the chemical composition of organic aerosol for selected events during the 2003 TORCH (Tropospheric Organic Chemistry Experiment) field campaign. The PTM incorporates the speciated emissions of 124 nonmethane anthropogenic volatile organic compounds (VOC) and three representative biogenic VOC, a highly-detailed representation of the atmospheric degradation of these VOC, the emission of primary organic aerosol (POA) material and the formation of secondary organic aerosol (SOA) material. SOA formation was represented by the transfer of semi and non-volatile oxidation products from the gas-phase to a condensed organic aerosol-phase, according to estimated thermodynamic equilibrium phase-partitioning characteristics for around 2000 reaction products. After significantly scaling all phase-partitioning coefficients, and assuming a persistent background organic aerosol (both required in order to match the observed organic aerosol loadings), the detailed chemical composition of the simulated SOA has been investigated in terms of intermediate oxygenated species in the Master Chemical Mechanism, version 3.1 ( MCM v3.1). For the various case studies considered, 90% of the simulated SOA mass comprises between ca. 70 and 100 multifunctional oxygenated species derived, in varying amounts, from the photooxidation of VOC of anthropogenic and biogenic origin. The anthropogenic contribution is dominated by aromatic hydrocarbons and the biogenic contribution by alpha-and beta-pinene (which also constitute surrogates for other emitted monoterpene species). Sensitivity in the simulated mass of SOA to changes in the emission rates of anthropogenic and biogenic VOC has also been investigated for 11 case study events, and the results have been compared to the detailed chemical composition data. The role of accretion chemistry in SOA formation, and its implications for the results of the present investigation, is discussed.