Aboriginal artefacts on the continental shelf reveal ancient drowned cultural landscapes in northwest Australia

This article reports Australia’s first confirmed ancient underwater archaeological sites from the continental shelf, located off the Murujuga coastline in north-western Australia. Details on two underwater sites are reported: Cape Bruguieres, comprising > 260 recorded lithic artefacts at depths down to −2.4 m below sea level, and Flying Foam Passage where the find spot is associated with a submerged freshwater spring at −14 m. The sites were discovered through a purposeful research strategy designed to identify underwater targets, using an iterative process incorporating a variety of aerial and underwater remote sensing techniques and diver investigation within a predictive framework to map the submerged landscape within a depth range of 0–20 m. The condition and context of the lithic artefacts are analysed in order to unravel their depositional and taphonomic history and to corroborate their in situ position on a pre-inundation land surface, taking account of known geomorphological and climatic processes including cyclone activity that could have caused displacement and transportation from adjacent coasts. Geomorphological data and radiometric dates establish the chronological limits of the sites and demonstrate that they cannot be later than 7000 cal BP and 8500 cal BP respectively, based on the dates when they were finally submerged by sea-level rise. Comparison of underwater and onshore lithic assemblages shows differences that are consistent with this chronological interpretation. This article sets a foundation for the research strategies and technologies needed to identify archaeological targets at greater depth on the Australian continental shelf and elsewhere, building on the results presented. Emphasis is also placed on the need for legislation to better protect and manage underwater cultural heritage on the 2 million square kilometres of drowned landscapes that were once available for occupation in Australia, and where a major part of its human history must lie waiting to be discovered

Supporting Spartina: Interdisciplinary perspective shows Spartina as a distinct solid genus

In 2014 a DNA-based phylogenetic study confirming the paraphyly of the grass subtribe Sporobolinae proposed the creation of a large monophyletic genus Sporobolus, including (among others) species previously included in the genera Spartina, Calamovilfa, and Sporobolus. Spartina species have contributed substantially (and continue contributing) to our knowledge in multiple disciplines, including ecology, evolutionary biology, molecular biology, biogeography, experimental ecology, environmental management, restoration ecology, history, economics, and sociology. There is no rationale so compelling to subsume the name Spartina as a subgenus that could rival the striking, global iconic history and use of the name Spartina for over 200 years. We do not agree with the arguments underlying the proposal to change Spartina to Sporobolus. We understand the importance of taxonomy and of formalized nomenclature and hope that by opening this debate we will encourage positive feedback that will strengthen taxonomic decisions with an interdisciplinary perspective. We consider the strongly distinct, monophyletic clade Spartina should simply and efficiently be treated as the genus Spartina

The Stakes in Bayh-Dole: Public Values Beyond the Pace of Innovation

Evaluation studies of the Bayh-Dole Act are generally concerned with the pace of innovation or the transgressions to the independence of research. While these concerns are important, I propose here to expand the range of public values considered in assessing Bayh-Dole and formulating future reforms. To this end, I first examine the changes in the terms of the Bayh-Dole debate and the drift in its design. Neoliberal ideas have had a definitive influence on U.S. innovation policy for the last thirty years, including legislation to strengthen patent protection. Moreover, the neoliberal policy agenda is articulated and justified in the interest of “competitiveness.” Rhetorically, this agenda equates competitiveness with economic growth and this with the public interest. Against that backdrop, I use Public Value Failure criteria to show that values such as political equality, transparency, and fairness in the distribution of the benefits of innovation, are worth considering to counter the “policy drift” of Bayh-Dole

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available