Spectral composition of shade light in coastal-zone oak forests in SE Bulgaria,and relationships with leaf area index: a first overview

Major knowledge gaps exist with respect to light-quality regimes in the coastal-zone Strandzha Quercus frainetto (Q.f.) forest region adjoining the southern Bulgarian Black Sea. This paper presents preliminary results that help narrow these gaps. In conjunction with leaf area index (LAI) field campaigns we undertook measurements with an array of 7 broad-band (ca 40 nm) sensors covering the range 0.40–0.94 μm, plus 1 sensor for UVB (0.297 μm peak) and 1 for photosynthetically active radiation (PAR). Measurements focused on inside-forest shade conditions at sites 0 to ca 15 km from the Black Sea and at altitudes up to ca 120 m above sea level. Some of the sites were also studied using a high-resolution spectroradiometer. A sequential measuring strategy was necessary. This involves potentially large uncertainties, here addressed through estimations of the variability around the sinusoidal course of daylight. Light-quality regimes were found to be in general support of earlier studies of deciduous forests. Our data from the broad-band sensors and from the spectroradiometer are mutually supportive. They indicate a stronger red-shift below Q.f. canopies than below canopies in enclaves dominated by Fagus orientalis and Pinus sylvestris. Transmission in the range 0.50–0.55 μm increases beneath the three types of canopies, most pronounced in the Q.f. case. Analysis of relationships between the inside-forest to open-field irradiance ratio and LAI supports the use of Beer’s Law. We found a fairly strong relationship between the red (0.66 μm) to far-red (0.73 μm) irradiance ratios (R/FR) and LAI for the Q.f. forest. In quantitative terms, the result is new for this Q.f. region, and suggests further research to explore whether a two-sensor approach (0.66 and 0.73 μm) might offer possibilities for further low-cost mapping of the spatio-temporal patterns of R/FR and LAI in Strandzha. Such mapping would assist in further studies of the region’s forest biogeochemistry and vitality.     

Joint multiple quantitative trait loci mapping for allometries of body compositions and metabolic traits to body weights in broiler

In order to map quantitative trait loci (QTLs) for allometries of body compositions and metabolic traits in chicken, we phenotypically characterize the allometric growths of multiple body components and metabolic traits relative to BWs using joint allometric scaling models and then establish random regression models (RRMs) to fit genetic effects of markers and minor polygenes derived from the pedigree on the allometric scalings. Prior to statistically inferring the QTLs for the allometric scalings by solving the RRMs, the LASSO technique is adopted to rapidly shrink most of marker genetic effects to zero. Computer simulation analysis confirms the reliability and adaptability of the so-called LASSO-RRM mapping method. In the F₂ population constructed by multiple families, we formulate two joint allometric scaling models of body compositions and metabolic traits, in which six of nine body compositions are tested as significant, while six of eight metabolic traits are as significant. For body compositions, a total of 14 QTLs, of which 9 dominant, were detected to be associated with the allometric scalings of drumstick, fat, heart, shank, liver and spleen to BWs; while for metabolic traits, a total of 19 QTLs also including 9 dominant be responsible for the allometries of T4, IGFI, IGFII, GLC, INS, IGR to BWs. The detectable QTLs or highly linked markers can be used to regulate relative growths of the body components and metabolic traits to BWs in marker-assisted breeding of chickens.     

Environmental regulation of surface conductance for evaporation from vegetation

We examine conductances for evaporation from both vegetation and soil in response to environmental variables. Data from a vertically-structured pristine forest of Nothofagus are presented as an example of the effects of biodiversity on the scaling of conductances between tiers of plant organisation. Available data sets of maximum leaf stomatal conductances (g _lmax ) and bulk vegetation surface conductances (G _smax ) are compared. Overall, the ratio G _smax /g _lmax is consistently close to 3 for seven major vegetation types of diverse structure. An analytical model accounts for this close relationship, and in particular how G _smax is conservative against changes in leaf area index because of the compensating decrease in plant canopy transpiration and increase in soil evaporation as leaf area index diminishes. The model is also successfully tested by comparison with canopy conductances of emergent trees measured in the Nothofagus forest. The constraint of vegetation surface conductance and evaporation via environmental regulation by irradiance, air saturation deficit and root zone water supply are discussed.     

An interaction index to predict turtle bycatch in a Mediterranean bottom trawl fishery

Incidental catch is the major threat to the survival of loggerhead turtles (Caretta caretta) in the Mediterranean and the main reason for their decline. More than 100,000 turtles are estimated to be caught annually due to fishing practices; 10–50% die. Bottom trawls are among the fishing gears exerting the worst impact on sea turtle populations, especially in the coastal waters of Tunisia and Libya, northern Adriatic Sea, the Mediterranean coastal areas of Turkey and Egypt, where the continental shelf is large and turtles in the demersal stage are commonly found also in winter. Seven adult-sized loggerhead turtles captured incidentally by bottom trawls in the central-northern Adriatic Sea and treated in rescue centres were tagged with satellite transmitters before release. In this paper Italian bottom trawl track data obtained from vessel monitoring systems (VMSs) were analysed by VMSbase R suite to identify the areas of maximum fishing effort in the Adriatic. These data were combined with satellite information on turtle distribution to provide an interaction index enabling prediction of potential trawl–turtle interaction hotspots and periods. The present pilot study can be considered as a risk-analysis approach directed at identifying the areas and times of possible trawling–turtle interactions in a Mediterranean trawl fishery. By identifying the areas and seasons at highest risk of turtle bycatch, the index here developed has the potential to provide key information to design and implement mitigation strategies. Vessel monitoring system is actually in force in several countries, therefore the approach here studied might have a worldwide application.     

Arsenic Bioaccumulation in Freshwater Fishes

The arsenic ambient water quality criterion (AWQC) for protection of human health via ingestion of aquatic organisms is currently 0.14 μ g/L. This AWQC is derived using a bioconcentration factor (BCF) of 44, which is a consumption-weighted average based on two data points for oysters and fish that was proposed by the U.S. Environmental Protection Agency in 1980 for broad application to freshwater and marine environments. This BCF is based on the assumption that bioaccumulation is a simple linear function of the exposure concentration. In the nearly quarter of a century since this BCF was promulgated, there have been additions to the arsenic bioaccumulation database and a broader scientific understanding of bioaccumulation mechanisms and how they can be applied to estimating tissue concentrations in aquatic organisms. From this database, we identified 12 studies of arsenic bioaccumulation in freshwater fishes in order to explore differences in laboratory-generated BCFs and field-generated bioaccumulation factors (BAFs) and to assess their relationship to arsenic concentrations in water. Our analysis indicates that arsenic concentrations in tissue and arsenic BAFs may be power functions of arsenic concentration in water. A power function indicates that the highest BCF values may occur at low background levels and may decrease as environmental concentrations increase above the ambient range.     

Evaluation of integrating topographic wetness index with backscattering coefficient of TerraSAR-X image for soil moisture estimation in a mountainous region

The estimation of soil moisture by using the backscattering coefficient of radar in a mountainous region is a challenging task due to the complex topography, which impacts the distribution of soil moisture and changes the backscattering coefficient. Complicated terrain can disturb empirical moisture estimation models, thereby, the resulting estimates of soil moisture are very unlikely reliable. This article proposed an innovative way of integration of the topographic wetness index (TWI) and the backscattering coefficient of soil obtained from the TerraSAR-X image, which improves the accuracy of measurement of the soil moisture. The standard estimation error and the coefficient of determination from the model were used to evaluate the performance of TWI. Our results show that the standard estimation error was decreased from: (1) 4.0% to 3.3% cm³ cm⁻³ at a depth of 5 cm and (2) 4.5% to 3.9% cm³ cm⁻³ at a depth of 10 cm. The most reliable estimation was observed at a depth of 5 cm, when it was compared with those of 0–5 cm, 10 cm and 15 cm. The TWI from the digital elevation model (DEM) is useful as a constraint condition for modeling work. This article concludes that the integration of the backscattering coefficient of soil with TWI can significantly reduce the uncertainty in the estimation of soil moisture in a mountainous region.     

Identification of soil quality indicators for assessing the effect of different tillage practices through a soil quality index in a semi-arid environment

Tillage is known to potentially affect soil quality in various ways. In this study, a soil quality index (SQI) was developed by quantifying several soil attributes either sensitive or insensitive to physical disturbance, using factor analysis as a dimension reduction technique, in order to discriminate different tillage systems. Soil properties including physical (MWD), chemical (pH, organic C, total N, available P and POM contents) and microbial (MBC, MBN, PCM, PNM and three enzymes) parameters were measured to establish a minimum data set (MDS) for the assessment of overall SQI. The soil attributes were determined on samples (0–20 cm depth) collected under moldboard (MP) and disk (DP) plows as conventional tillage (CT), and rotary (RP) and chisel (CP) plows as reduced tillage (RT) systems with a similar plant C input rate and cover crop over a period of six years (2005–2011) in a semi-arid calcareous soil (Calcixerepts) from Central Iran. Results indicated a clear difference in soil quality among the tillage systems with a significant increase of SQI under RT over time, particularly under CP practices. Although RT improved most soil microbial attributes, not all attributes contributed to SQI because of their close interrelationship. The final SQI consisted only of geometric mean of microbial activity (GMA, the square root of the product of PCM and PNM) and geometric mean of enzyme activity (GME, the cube root of the product of enzyme activities). Soil GME and GMA were found to be as key indicators contributing 55% and 36% to SQI, respectively. Therefore, the GME and GMA were the most important indicators effectively discriminating tillage systems, and could be used to monitor the enhancement of soil quality under RT in this semiarid environment. The influence of tillage year on SQI was greater than that of tillage practices. In conclusion, RT systems were characterized by a higher value of SQI, suggesting a good recovery of soil capacity and functions after abandoning CT in the studied area. Smallholder farmers should therefore be aware of the potential for high soil quality in future as a result of continuing RT systems, especially with surface tillage using CP practices.