What image features guide lightness perception?

Lightness constancy is the ability to perceive black and white surface colors under a wide range of lighting conditions. This fundamental visual ability is not well understood, and current theories differ greatly on what image features are important for lightness perception. Here we measured classification images for human observers and four models of lightness perception to determine which image regions influenced lightness judgments. The models were a high-pass-filter model, an oriented difference-of-Gaussians model, an anchoring model, and an atmospheric-link-function model. Human and model observers viewed three variants of the argyle illusion (Adelson, 1993) and judged which of two test patches appeared lighter. Classification images showed that human lightness judgments were based on local, anisotropic stimulus regions that were bounded by regions of uniform lighting. The atmospheric-link-function and anchoring models predicted the lightness illusion perceived by human observers, but the high-pass-filter and oriented-difference-of-Gaussians models did not. Furthermore, all four models produced classification images that were qualitatively different from those of human observers, meaning that the model lightness judgments were guided by different image regions than human lightness judgments. These experiments provide a new test of models of lightness perception, and show that human observers' lightness computations can be highly local, as in low-level models, and nevertheless depend strongly on lighting boundaries, as suggested by midlevel models.York University Librarie

Icelandic debris flow and their relationship to martian gullies

Abstract not available

Stratigraphical evidence of Elysium sea ice from HiRise images

Abstract not available

Morphological evidence for a sea-ice origin for Elysium Planitia platy terrain

Abstract not available

Recolonizing wolves and mesopredator suppression of coyotes:impacts on pronghorn population dynamics

Food web theory predicts that the loss of large carnivores may contribute toelevated predation rates and, hence, declining prey populations, through the process ofmesopredator release. However, opportunities to test predictions of the mesopredator releasehypothesis are rare, and the extent to which changes in predation rates influence preypopulation dynamics may not be clear due to a lack of demographic information on the preypopulation of interest. We utilized spatial and seasonal heterogeneity in wolf distribution andabundance to evaluate whether mesopredator release of coyotes (Canis latrans), resulting fromthe extirpation of wolves (Canis lupus) throughout much of the United States, contributes tohigh rates of neonatal mortality in ungulates. To test this hypothesis, we contrasted causes ofmortality and survival rates of pronghorn (Antilocapra americana) neonates captured at wolf-free and wolf-abundant sites in western Wyoming, USA, between 2002 and 2004. We thenused these data to parameterize stochastic population models to heuristically assess the impactof wolves on pronghorn population dynamics due to changes in neonatal survival. Coyotepredation was the primary cause of mortality at all sites, but mortality due to coyotes was 34%lower in areas utilized by wolves (P , 0.001). Based on simulation modeling, the realizedpopulation growth rate was 0.92 based on fawn survival in the absence of wolves, and 1.06 atsites utilized by wolves. Thus, wolf restoration is predicted to shift the trajectory of thepronghorn population from a declining to an increasing trend. Our results suggest thatreintroductions of large carnivores may influence biodiversity through effects on preypopulations mediated by mesopredator suppression. In addition, our approach, whichcombines empirical data on the population of interest with information from other datasources, demonstrates the utility of using simulation modeling to more fully evaluateecological theories by moving beyond estimating changes in vital rates to analyses ofpopulation-level impacts

Indirect Effects and Traditional Trophic Cascades: a Test Involving Wolves, Coyotes, and Pronghorn

The traditional trophic cascades model is based on consumer - resource interactions at each link in a food chain. However, trophic-level interactions, such as mesocarnivore release resulting from intraguild predation, may also be important mediators of cascades. From September 2001 to August 2004, we used spatial and seasonal heterogeneity in wolf distribution and abundance in the southern Greater Yellowstone Ecosystem to evaluate whether mesopredator release of coyotes ( Canis latrans), resulting from the extirpation of wolves ( Canis lupus), accounts for high rates of coyote predation on pronghorn ( Antilocapra americana) fawns observed in some areas. Results of this ecological perturbation in wolf densities, coyote densities, and pronghorn neonatal survival at wolf-free and wolf-abundant sites support the existence of a species-level trophic cascade. That wolves precipitated a trophic cascade was evidenced by fawn survival rates that were four-fold higher at sites used by wolves. A negative correlation between coyote and wolf densities supports the hypothesis that interspecific interactions between the two species facilitated the difference in fawn survival. Whereas densities of resident coyotes were similar between wolf-free and wolf-abundant sites, the abundance of transient coyotes was significantly lower in areas used by wolves. Thus, differential effects of wolves on solitary coyotes may be an important mechanism by which wolves limit coyote densities. Our results support the hypothesis that mesopredator release of coyotes contributes to high rates of coyote predation on pronghorn fawns, and demonstrate the importance of alternative food web pathways in structuring the dynamics of terrestrial systems

Global Dynamical Structure Reconstruction from Reconstructed Dynamical Structure Subnetworks: Applications to Biochemical Reaction Networks

In this paper we consider the problem of network reconstruction, with applications to biochemical reaction networks. In particular, we consider the problem of global network reconstruction when there are a limited number of sensors that can be used to simultaneously measure state information. We introduce dynamical structure functions as a way to formulate the network reconstruction problem and motivate their usage with an example physical system from synthetic biology. In particular, we argue that in synthetic biology research, network verification is paramount to robust circuit operation and thus, network reconstruction is an invaluable tool. Nonetheless, we argue that existing approaches for reconstruction are hampered by limited numbers of biological sensors with high temporal resolution. In this way, we motivate the global network reconstruction problem using partial network information and prove that by performing a series of reconstruction experiments, where each experiment reconstructs a subnetwork dynamical structure function, the global dynamical structure function can be recovered in most cases. We illustrate these reconstruction techniques on a recently developed four gene biocircuit, an event detector, and show that it is capable of differentiating the temporal order of input events

The Formation and Evolution of Planetary Systems: Description of the Spitzer Legacy Science Database

We present the science database produced by the Formation and Evolution of Planetary Systems (FEPS) Spitzer Legacy program. Data reduction and validation procedures for the IRAC, MIPS, and IRS instruments are described in detail. We also derive stellar properties for the FEPS sample from available broad-band photometry and spectral types, and present an algorithm to normalize Kurucz synthetic spectra to optical and near-infrared photometry. The final FEPS data products include IRAC and MIPS photometry for each star in the FEPS sample and calibrated IRS spectra.Comment: 64 pages, 12 figures, 5 tables; accepted for publication in ApJ