Sugarcane is an important economic resource for many tropical countries and optimizing plantations is a serious concern with economic and environmental benefits. One of the best ways to optimize the use of resources in those plantations is to minimize the occurrence of gaps. Typically, gaps open in the crop canopy because of damaged rhizomes, unsuccessful sprouting or death young stalks. In order to avoid severe yield decrease, farmers need to fill the gaps with new plants. Mapping gap density is therefore critical to evaluate crop planting quality and guide replanting. Current field practices of linear gap evaluation are very labor intensive and cannot be performed with sufficient intensity as to provide detailed spatial information for mapping, which makes replanting difficult to perform. Others have used sensors carried by land vehicles to detect gaps, but these are complex and require circulating over the entire area. We present a method based on processing digital mosaics of conventional images acquired from a small Unmanned Aerial Vehicle (UAV) that produced a map of gaps at 23.5 cm resolution in a study area of 8.7 ha with 92.9% overall accuracy. Linear Gap percentage estimated from this map for a grid with cells of 10 mˆ10 m linearly correlates with photo-interpreted linear gap percentage with a coefficient of determination (R 2 )= 0.9; a root mean square error (RMSE) = 5.04; and probability (p) << 0.01. Crop Planting Quality levels calculated from image-derived gaps agree with those calculated from a photo-interpreted version of currently used field methods (Spearman coefficient = 0.92). These results clearly demonstrate the effectiveness of processing mosaics of Unmanned Aerial System (UAS) images for mapping gap density and, together with previous studies using satellite and hand-held spectroradiometry, suggests the extension towards multi-spectral imagery to add insight on plant condition.

The aquatic gastropod mollusc, Pyrgophorus coronatus, may perform an important role in the transmission of an emergent ocular pathology among fishes in Lake Apoyo, Nicaragua. This disease emerged after an introduction of tilapia (Oreochromis niloticus) and the subsequent loss of Chara sp. beds in the lake. We compared the mollusc population densities in three habitats (sandy/muddy substrates, rocks, and Chara vegetation) at varying depths (1.5, 10, 20, and 30 m) in two volcanic crater lakes in Nicaragua: Lake Apoyo and Lake Xiloa, where lower numbers of affected fishes were found and tilapia has not been introduced. Duplicate samples at 1.5 m depth were taken in each habitat monthly for a year, and triplicate samples for bathymetric analysis of snail populations were performed during August, 2005. Samples of fixed surface area were filtered in a 0.4 cm size screen and live snails were counted from each sample. The preferred snail habitat in both lakes, Chara beds, was vastly reduced in Lake Apoyo via consumption by introduced Nile tilapia (Oreochromis niloticus). Structureless sandy substrates (mean ± standard error 3.1±1.3 ind/m 2) had lower population densities than other habitats in Lake Xiloá (rocks 590.9±185.3 ind/m 2 ; vegetation 3 686.5±698.2 ind/m 2 ; ANOVA I, p<0.01 in both cases) but this difference was attenuated in Lake Apoyo (sand 384.4±111.1 ind/m 2 ; rocks 1 480.4±384.8 ind/m 2 ; 0.01