Temporal and spatial variation in the Nazaré Canyon (Western Iberian margin): Inter-annual and canyon heterogeneity effects on meiofauna biomass and diversity

The Nazaré Canyon on the Portuguese Margin (NE Atlantic) was sampled during spring-summer for three consecutive years (2005–2007), permitting the first inter-annual study of the meiofaunal communities at the Iberian Margin at two abyssal depths (~3500 m and ~4400 m). Using new and already published data, the meiofauna standing stocks (abundance and biomass) and nematode structural and functional diversity were investigated in relation to the sediment biogeochemistry (e.g. organic carbon, nitrogen, chlorophyll a, phaeopigments) and grain size. A conspicuous increase in sand content from 2005 to 2006 and decrease of phytodetritus at both sites, suggested the occurrence of one or more physical disturbance events. Nematode standing stocks and trophic diversity decreased after these events, seemingly followed by a recovery/recolonisation period in 2007, which was strongly correlated with an increase in the quantity and bioavailability of phytodetrital organic matter supplied. Changes in meiofauna assemblages, however, also differed between stations, likely because of the contrasting hydrodynamic and food supply conditions. Higher meiofauna and nematode abundances, biomass and trophic complexity were found at the shallowest canyon station, where the quantity, quality and bioavailability of food material were higher than at the deeper site. The present results suggest that even though inter-annual variations in the sedimentary environment can regulate the meiofauna in the abyssal Nazaré Canyon, heterogeneity between sampling locations in the canyon were more pronounced.

Data processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment

Remote sensing airborne hyperspectral data are routinely used for applications including algorithm development for satellite sensors, environmental monitoring and atmospheric studies. Single flight lines of airborne hyperspectral data are often in the region of tens of gigabytes in size. This means that a single aircraft can collect terabytes of remotely sensed hyperspectral data during a single year. Before these data can be used for scientific analyses, they need to be radiometrically calibrated, synchronised with the aircraft's position and attitude and then geocorrected. To enable efficient processing of these large datasets the UK Airborne Research and Survey Facility has recently developed a software suite, the Airborne Processing Library (APL), for processing airborne hyperspectral data acquired from the Specim AISA Eagle and Hawk instruments. The APL toolbox allows users to radiometrically calibrate, geocorrect, reproject and resample airborne data. Each stage of the toolbox outputs data in the common Band Interleaved Lines (BILs) format, which allows its integration with other standard remote sensing software packages. APL was developed to be user-friendly and suitable for use on a workstation PC as well as for the automated processing of the facility; to this end APL can be used under both Windows and Linux environments on a single desktop machine or through a Grid engine. A graphical user interface also exists. In this paper we describe the Airborne Processing Library software, its algorithms and approach. We present example results from using APL with an AISA Eagle sensor and we assess its spatial accuracy using data from multiple flight lines collected during a campaign in 2008 together with in situ surveyed ground control points.

Spatial Variability of Durum Wheat Yield as Related to Soil Parameters in an Organic Field

The yield in organic farming is generally much lower than its potential, which is due to its specificity. The objective of the present study was to quantify the yield spatial variation of wheat and relate it to soil parameters in an organic farm located in the north of the Negev Desert. Soil samples were gathered in a triangular grid at three time intervals. Yields were measured at 73 georeferenced points before the actual harvest. Several thematic maps of soil and yield parameters were produced using geographic information system and geostatistical methods. The strongest spatial correlation was found in the weight of 1000 grains and the weakest was in carbon flow. Temporal relationships were found between soil nitrate concentration, soil water content, and leaf area index. Wheat yield varied from 1.11 to 2.84 Mg ha(-1) and this remarkable variation indicates that the spatial analysis of soil and yield parameters is significant in organic agriculture.