Generalized estimators of avian abundance from count survey data

I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture-recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed

P2X receptor trafficking in neurons is subunit specific

P2X receptors within the CNS mediate excitatory synaptic transmission and also act presynaptically to modulate neurotransmitter release. We have studied the targeting and trafficking of P2X4 and P2X2 receptors heterologously expressed in cultured olfactory bulb neurons. Homomeric P2X4 receptors had a punctate distribution, and many of the puncta colocalized with early endosomes. In contrast, P2X2 receptors were primarily localized at the plasma membrane. By antibody-labeling of surface receptors in living neurons, we showed that P2X4 receptors undergo rapid constitutive internalization and subsequent reinsertion into the plasma membrane, whereas P2X2 receptors were not regulated in such a way. The internalization of P2X4 receptors was dynamin-dependent, and the binding of ATP enhanced the basal rate of retrieval in a Ca2+-independent manner. The presence of the P2X4 subunit in a P2X4/6 heteromer governed the trafficking properties of the receptor. P2X receptors acted presynaptically to enhance the release of glutamate, suggesting that the regulated cycling of P2X4-containing receptors might provide a mechanism for modulation of synaptic transmission

Estimadores generalizados de abundancia en aves a partir de datos de estudios de recuento

I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture–recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.En el presente estudio se analiza la modelación de la abundancia en aves mediante datos de recuento de aves, referenciados espacialmente y obtenidos a partir de protocolos comunes, como los de captura–recaptura, muestreo por observadores múltiples, muestreo por eliminación y recuentos de puntos simples. Las muestras de pequeño tamaño, así como el amplio número de parámetros, han propiciado numerosos análisis que no tienen en cuenta la indexación espacial de los datos y, por consiguiente, no proporcionan un tratamiento adecuado de la estructura espacial. En este trabajo se describe un marco general para la modelación de datos replicados en el espacio, que considera la abundancia local como un proceso aleatorio, todo ello basado en el punto de vista de que el conjunto de poblaciones locales referenciadas espacialmente (en los lugares de toma de muestras) constituye una metapoblación. De este modo, la atención puede centrarse en el desarrollo de un modelo para la variación en la abundancia local que sea independiente del protocolo de muestreo que se esté utilizando. La estructura del modelo metapoblacional, en combinación con el modelo de generación de datos, define un modelo jerárquico simple que puede analizarse mediante el empleo de métodos convencionales. El marco de modelación propuesto es de carácter general, en el sentido de que permite considerar amplias clases de modelos metapoblacionales, covariantes del nivel del emplazamiento sobre datos de detección, y la abundancia, pudiendo obtenerse estimaciones de abundancia y cantidades relacionadas para emplazamientos de muestreo, grupos de emplazamientos y emplazamientos no muestreados. A tal efecto, se incluyen dos breves ejemplos; el primero trata de los recuentos de puntos simples, mientras que el segundo se basa en los recuentos por extracción temporal. También se apunta la posibilidad de ampliar estos modelos a sistemas abiertos

FerriTag is a new genetically-encoded inducible tag for correlative light-electron microscopy

A current challenge is to develop tags to precisely visualize proteins in cells by light and electron microscopy. Here, we introduce FerriTag, a genetically-encoded chemically-inducible tag for correlative light-electron microscopy. FerriTag is a fluorescent recombinant electron-dense ferritin particle that can be attached to a protein-of-interest using rapamycin-induced heterodimerization. We demonstrate the utility of FerriTag for correlative light-electron microscopy by labeling proteins associated with various intracellular structures including mitochondria, plasma membrane, and clathrin-coated pits and vesicles. FerriTagging has a good signal-to-noise ratio and a labeling resolution of approximately 10 nm. We demonstrate how FerriTagging allows nanoscale mapping of protein location relative to a subcellular structure, and use it to detail the distribution and conformation of huntingtin-interacting protein 1 related (HIP1R) in and around clathrin-coated pits

Spatially explicit models for inference about density in unmarked or partially marked populations

Recently developed spatial capture-recapture (SCR) models represent a major advance over traditional capture-recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5-10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19-1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density - rather, spatial dependence can be informative about individual distribution and density.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS610 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Artificial maturation of iron- and sulfur-rich Mars analogues: Implications for the diagenetic stability of biopolymers and their detection with pyrolysis gas chromatography–mass spectrometry

Acidic iron- and sulfur-rich streams are appropriate analogues for the late Noachian and early Hesperian periods of martian history, when Mars exhibited extensive habitable environments. Any past life on Mars may have left behind diagnostic evidence of life that could be detected at the present day. For effective preservation, these remains must have avoided the harsh radiation flux at the martian surface, survived geological storage for billions of years, and remained detectable within their geochemical environment by analytical instrument suites used on Mars today, such as thermal extraction techniques. We investigated the detectability of organic matter within sulfur stream sediments that had been subjected to artificial maturation by hydrous pyrolysis. After maturation, the samples were analyzed by pyrolysis–gas chromatography–mass spectrometry (py-GC-MS) to determine whether organic matter could be detected with this commonly used technique. We find that macromolecular organic matter can survive the artificial maturation process in the presence of iron- and sulfur-rich minerals but cannot be unambiguously distinguished from abiotic organic matter. However, if jarosite and goethite are present in the sulfur stream environment, they interfere with the py-GC-MS detection of organic compounds in these samples. Clay reduces the obfuscating effect of the oxidizing minerals by providing nondeleterious adsorption sites. We also find that after a simple alkali and acid leaching process that removes oxidizing minerals such as iron sulfates, oxides, and oxyhydroxides, the sulfur stream samples exhibit much greater organic responses during py-GC-MS in terms of both abundance and diversity of organic compounds, such as the detection of hopanes in all leached samples. Our results suggest that insoluble organic matter can be preserved over billions of years of geological storage while still retaining diagnostic organic information, but sample selection strategies must either avoid jarosite- and goethite-rich outcrops or conduct preparative chemistry steps to remove these oxidants prior to analysis by thermal extraction techniques