Automated extraction of bank angles from bird‐borne video footage using open‐source software

The use of miniaturized video cameras to study the at‐sea behavior of flying seabirds has increased in recent years. These cameras allow researchers to record several behaviors that were not previously possible to observe. However, video recorders produce large amounts of data and videos can often be time‐consuming to analyze. We present a new technique using open‐source software to extract bank angles from bird‐borne video footage. Bank angle is a key facet of dynamic soaring, which allows albatrosses and petrels to efficiently search vast areas of ocean for food. Miniaturized video cameras were deployed on 28 Wandering Albatrosses (Diomedea exulans) on Marion Island (one of the two Prince Edward Islands) from 2016 to 2018. The OpenCV library for the Python programming language was used to extract the angle of the horizon relative to the bird’s body (= bank angle) from footage when the birds were flying using a series of steps focused on edge detection. The extracted angles were not significantly different from angles measured manually by three independent observers, thus being a valid method to measure bank angles. Image quality, high wind speeds, and sunlight all influenced the accuracy of angle estimates, but post‐processing eliminated most of these errors. Birds flew most often with cross‐winds (58%) and tailwinds (39%), resulting in skewed distributions of bank angles when birds turned into the wind more often. Higher wind speeds resulted in extreme bank angles (maximum observed was 94°). We present a novel method for measuring postural data from seabirds that can be used to describe the fine‐scale movements of the dynamic‐soaring cycle. Birds appeared to alter their bank angle in response to varying wind conditions to counter wind drift associated with the prevailing westerly winds in the Southern Ocean. These data, in combination with fine‐scale positional data, may lead to new insights into dynamic‐soaring flight.     

Pollen-based biome reconstruction for southern Europe and Africa 18,000 yr bp

Pollen data from 18,000 ¹⁴C yr bp were compiled in order to reconstruct biome distributions at the last glacial maximum in southern Europe and Africa. Biome reconstructions were made using the objective biomization method applied to pollen counts using a complete list of dryland taxa wherever possible. Consistent and major differences from present‐day biomes are shown. Forest and xerophytic woods/scrub were replaced by steppe, both in the Mediterranean region and in southern Africa, except in south‐western Cape Province where fynbos (xerophytic scrub) persisted. Sites in the tropical highlands, characterized today by evergreen forest, were dominated by steppe and/or xerophytic vegetation (cf. today’s Ericaceous belt and Afroalpine grassland) at the last glacial maximum. Available data from the tropical lowlands are sparse but suggest that the modern tropical rain forest was largely replaced by tropical seasonal forest while the modern seasonal or dry forests were encroached on by savanna or steppe. Montane forest elements descended to lower elevations than today.     

FOSSIL WOOD OF ROBINIA AND GLEDITSIA FROM THE TERTIARY OF MONTANA

Prakash , U., E. S. Barghoorn , and R. A. Scott . (Harvard U., Cambridge, Mass.) Fossil wood of Robinia and Gleditsia from the Tertiary of Montana . Amer. Jour. Bot. 49(7): 692–696. Illus. 1962.—Fossil woods representing 2 genera of the Leguminosae, Robinia Linnaeus and Gleditsia Clayton, have been identified from Tertiary beds in southern Montana. These woods are noteworthy owing to their exceptionally fine structural preservation and from the standpoint of their paleogeographical distribution. Neither genus now lives in the region of Montana.     

A simple and novel interpretation of the three-dimensional structure of globular proteins based on quantum-mechanical computations on small model molecules. I

It is suggested that the three-dimensional structure of globular proteins is partly determined by a framework of strengthened hydrogen bonds that involves both ionic side chains and water molecules in addition to the polypeptide backbone. This conclusion follows from a combination of the results of ab initio molecular-orbital computations on small model molecules and high-accuracy x-ray data on the rubredoxin molecule. The computations yield the idea of hydrogen-bonded bridges that are built from tens of atoms, and the experimental information yields the idea that the bridges are assembled into clusters, each of which is built from hundreds of atoms. Some 10 such clusters then form a globular protein.     

Assessing Greater Sage-Grouse Selection of Brood-Rearing Habitat Using Remotely-Sensed Imagery: Can Readily Available High-Resolution Imagery Be Used to Identify Brood-Rearing Habitat Across a Broad Landscape?

Greater sage-grouse populations have decreased steadily since European settlement in western North America. Reduced availability of brood-rearing habitat has been identified as a limiting factor for many populations. We used radio-telemetry to acquire locations of sage-grouse broods from 1998 to 2012 in Strawberry Valley, Utah. Using these locations and remotely-sensed NAIP (National Agricultural Imagery Program) imagery, we 1) determined which characteristics of brood-rearing habitat could be used in widely available, high resolution imagery 2) assessed the spatial extent at which sage-grouse selected brood-rearing habitat, and 3) created a predictive habitat model to identify areas of preferred brood-rearing habitat. We used AIC model selection to evaluate support for a list of variables derived from remotely-sensed imagery. We examined the relationship of these explanatory variables at three spatial extents (45, 200, and 795 meter radii). Our top model included 10 variables (percent shrub, percent grass, percent tree, percent paved road, percent riparian, meters of sage/tree edge, meters of riparian/tree edge, distance to tree, distance to transmission lines, and distance to permanent structures). Variables from each spatial extent were represented in our top model with the majority being associated with the larger (795 meter) spatial extent. When applied to our study area, our top model predicted 75% of naïve brood locations suggesting reasonable success using this method and widely available NAIP imagery. We encourage application of our methodology to other sage-grouse populations and species of conservation concern.