Epiphytic biomass of a tropical montane forest varies with topography

The spatial heterogeneity of tropical forest epiphytes has rarely been quantified in terms of biomass. In particular, the effect of topographic variation on epiphyte biomass is poorly known, although forests on ridges and ravines can differ drastically in stature and exposure. In an Ecuadorian lower montane forest we quantified epiphytic biomass along two gradients: (1) the twig-branch-trunk trajectory, and (2) the ridge-ravine gradient. Twenty-one trees were sampled in each of three forest types (ridge, slope, ravine positions). Their epiphytic biomass was extrapolated to stand level based on basal area-epiphyte load relationships, with tree basal areas taken from six plots of 400 m 2 each per forest type. Our results document the successional addition and partial replacement of lichens by bryophytes, angiosperms and finally dead organic matter along the twig-branch-trunk trajectory. Despite having the highest tree basal area, total epiphytic biomass (mean ± SD) of ravine forest was significantly lower (2.6 ± 0.7 Mg ha -1) than in mid-slope forest (6.3 ± 1.1 Mg ha -1) and ridge forest (4.4 ± 1.6 Mg ha -1), whereas maximum bryophyte water storage capacity was significantly higher. We attribute this pattern to differences in forest dynamics, stand structure and microclimate. Although our study could not differentiate between direct effects of slope position (nutrient availability, mesoclimate) and indirect effects (stand structure and dynamics), it provides evidence that fine-scale topography needs to be taken into account when extrapolating epiphytic biomass and related matter fluxes from stand-level data to the regional scale. © Copyright Cambridge University Press 2011

The Cyborg Astrobiologist: Testing a Novelty-Detection Algorithm on Two Mobile Exploration Systems at Rivas Vaciamadrid in Spain and at the Mars Desert Research Station in Utah

(ABRIDGED) In previous work, two platforms have been developed for testing computer-vision algorithms for robotic planetary exploration (McGuire et al. 2004b,2005; Bartolo et al. 2007). The wearable-computer platform has been tested at geological and astrobiological field sites in Spain (Rivas Vaciamadrid and Riba de Santiuste), and the phone-camera has been tested at a geological field site in Malta. In this work, we (i) apply a Hopfield neural-network algorithm for novelty detection based upon color, (ii) integrate a field-capable digital microscope on the wearable computer platform, (iii) test this novelty detection with the digital microscope at Rivas Vaciamadrid, (iv) develop a Bluetooth communication mode for the phone-camera platform, in order to allow access to a mobile processing computer at the field sites, and (v) test the novelty detection on the Bluetooth-enabled phone-camera connected to a netbook computer at the Mars Desert Research Station in Utah. This systems engineering and field testing have together allowed us to develop a real-time computer-vision system that is capable, for example, of identifying lichens as novel within a series of images acquired in semi-arid desert environments. We acquired sequences of images of geologic outcrops in Utah and Spain consisting of various rock types and colors to test this algorithm. The algorithm robustly recognized previously-observed units by their color, while requiring only a single image or a few images to learn colors as familiar, demonstrating its fast learning capability.Comment: 28 pages, 12 figures, accepted for publication in the International Journal of Astrobiolog