Community-specific "desired" states for seagrasses through cycles of loss and recovery

Seagrass habitats provide critical ecosystem services, yet there is ongoing concern over mounting pressures and continuing degradation. Defining a desired state for these habitats is a key step in implementing appropriate management but is often difficult given the challenges of available data and an evaluation of where to set benchmarks. We use more than 20 years of historical seagrass biomass data (1995–2018) for the diverse seagrass communities of Australia's Great Barrier Reef World Heritage Area (GBRWHA) to develop desired state benchmarks. Desired state for seagrass biomass was estimated for 25 of 36 previously defined seagrass communities with the remainder having insufficient data. Desired state varied by more than one order of magnitude between community types and was influenced by the mix of species in the communities and the range of environmental conditions. We identify a historical, decadal-scale cycle of decline with recovery to desired state in coastal intertidal communities. In contrast a number of the estuary and coastal subtidal communities have not recovered to desired state biomass. Understanding a historical context is critically important for setting benchmarks and making informed management decisions on the present state of seagrass in the GBRWHA. The approach we have developed is scalable for monitoring, management and assessment of pressures for other management areas and for other jurisdictions. Our results guide conservation planning through prioritization of the at-risk seagrass communities that are continuing to fall below their desired state

Bird nests as botanical time capsules: DNA barcoding identifies the contents of contemporary and historical nests

Bird nests in natural history collections are an abundant yet vastly underutilized source of genetic information. We sequenced the nuclear ribosomal internal transcribed spacer to identify plant species used as nest material in two contemporary (2003 and 2018) and two historical (both 1915) nest specimens constructed by Song Sparrows (Melospiza melodia) and Savannah Sparrows (Passerculus sandwichensis). A total of 13 (22%) samples yielded single, strong bands that could be identified using GenBank resources: six plants (Angiospermae), six green algae (Chlorophyta), and one ciliate (Ciliophora). Two native plant species identified in the nests included Festuca microstachys, which was introduced to the nest collection site by restoration practitioners, and Rosa californica, identified in a nest collected from a lost habitat that existed about 100 years ago. Successful sequencing was correlated with higher sample mass and DNA quality, suggesting future studies should select larger pieces of contiguous material from nests and materials that appear to have been fresh when incorporated into the nest. This molecular approach was used to distinguish plant species that were not visually identifiable, and did not require disassembling the nest specimens as is a traditional practice with nest material studies. The many thousands of nest specimens in natural history collections hold great promise as sources of genetic information to address myriad ecological questions

Series solutions for a static scalar potential in a Salam-Sezgin Supergravitational hybrid braneworld

The static potential for a massless scalar field shares the essential features of the scalar gravitational mode in a tensorial perturbation analysis about the background solution. Using the fluxbrane construction of [8] we calculate the lowest order of the static potential of a massless scalar field on a thin brane using series solutions to the scalar field's Klein Gordon equation and we find that it has the same form as Newton's Law of Gravity. We claim our method will in general provide a quick and useful check that one may use to see if their model will recover Newton's Law to lowest order on the brane.Comment: 5 pages, no figure

A spatial analysis of seagrass habitat and community diversity in the Great Barrier Reef World Heritage Area

The Great Barrier Reef World Heritage Area (GBRWHA) in north eastern Australia spans 2,500 km of coastline and covers an area of ~350,000 km2. It includes one of the world’s largest seagrass resources. To provide a foundation to monitor, establish trends and manage the protection of seagrass meadows in the GBRWHA we quantified potential seagrass community extent using six random forest models that include environmental data and seagrass sampling history. We identified 88,331 km2 of potential seagrass habitat in intertidal and subtidal areas: 1,111 km2 in estuaries, 16,276 km2 in coastal areas, and 70,934 km2 in reef areas. Thirty-six seagrass community types were defined by species assemblages within these habitat types using multivariate regression tree models. We show that the structure, location and distribution of the seagrass communities is the result of complex environmental interactions. These environmental conditions include depth, tidal exposure, latitude, current speed, benthic light, proportion of mud in the sediment, water type, water temperature, salinity, and wind speed. Our analysis will underpin spatial planning, can be used in the design of monitoring programs to represent the diversity of seagrass communities and will facilitate our understanding of environmental risk to these habitats

Seagrass mapping synthesis: a resource for coastal management in the Great Barrier Reef World Heritage Area

This project provides an up to date synthesis of the available information on seagrass in the Great Barrier Reef World Heritage Area (GBRWHA). It brings together more than 30 years of spatial information and data collection into easy to use spatial GIS layers that provide key information on species, meadow type and age and reliability of the data. The project provides: Seagrass site and meadow-specific data in Geographic Information System (GIS) layers to provide seagrass data to inform research analysis and management advice. A site layer that includes >66,000 individual survey sites with information including latitude/longitude, Natural Resource Management region, site depth, seagrass presence/absence, dominant seagrass species, presence/absence of individual species, survey date, survey method, and data custodian. A meadow layer that includes 1169 individual and/or composite seagrass meadows with information including individual meadow persistence, meadow location (intertidal/subtidal), meadow density based on mean biomass and/or mean percent cover, meadow area, dominant seagrass species, seagrass species present, range of survey dates, survey method, and data custodian. Metadata to enable interpretation of the information and to identify the original data custodians for assistance with interpretation. Outcomes: This study consolidates all available seagrass spatial data for the GBRWHA collected from 1984 to December 2014 by the TropWATER Seagrass Group and CSIRO in a GIS database. It assembles and documents the state of spatial knowledge of seagrass in the GBRWHA. The spatial data is based on methods developed by TropWATER and CSIRO for seagrass habitat surveys of subtidal meadows, and TropWATER methods for intertidal surveys. Methods include sampling by boat (free divers, underwater video camera, grabs, sled with net sampling), helicopter and walking. 447,530 hectares of seagrasses were mapped (modelled deep water seagrass areas are not included in area figures in this report) within the GBRWHA; much of which provides habitat for commercial and traditional fishery species, and an important food resource for dugong and green turtle populations. Data is included for twelve seagrass species from three families. Seagrass was present at 39% of all sites visited. The study identifies areas where much of the data available for management is more than 20 years old or where there are specific habitats unsurveyed. Large areas of central and northern Queensland require updating. Several key habitat types such as reef platform seagrass meadows are poorly represented in the data

Dynamics of a deep-water seagrass population on the Great Barrier Reef: annual occurrence and response to a major dredging program

Global seagrass research efforts have focused on shallow coastal and estuarine seagrass populations where alarming declines have been recorded. Comparatively little is known about the dynamics of deep-water seagrasses despite evidence that they form extensive meadows in some parts of the world. Deep-water seagrasses are subject to similar anthropogenic threats as shallow meadows, particularly along the Great Barrier Reef lagoon where they occur close to major population centres. We examine the dynamics of a deep-water seagrass population in the GBR over an 8 year period during which time a major capital dredging project occurred. Seasonal and inter-annual changes in seagrasses were assessed as well as the impact of dredging. The seagrass population was found to occur annually, generally present between July and December each year. Extensive and persistent turbid plumes from a large dredging program over an 8 month period resulted in a failure of the seagrasses to establish in 2006, however recruitment occurred the following year and the regular annual cycle was re-established. Results show that despite considerable inter annual variability, deep-water seagrasses had a regular annual pattern of occurrence, low resistance to reduced water quality but a capacity for rapid recolonisation on the cessation of impacts

Synthesizing 35 years of seagrass spatial data from the Great Barrier Reef World Heritage Area, Queensland, Australia

The Great Barrier Reef World Heritage Area in Queensland, Australia contains globally significant seagrasses supporting key ecosystem services, including habitat and food for threatened populations of dugong and turtle. We compiled 35 years of data in a spatial database, including 81,387 data points with georeferenced seagrass and species presence/absence, depth, dominant sediment type, and collection date. We include data collected under commercial contract that have not been publicly available. Twelve seagrass species were recorded. The deepest seagrass was found at 76 m. Seagrass meadows are at risk from anthropogenic, climate and weather processes. Our database is a valuable resource that provides coastal managers and the global marine community with a long-term spatial resource describing seagrass populations from the mid-1980s against which to benchmark change. We address the data issues involved in hindcasting over 30 years to ensure confidence in the accuracy and reliability of data included

A report card approach to describe temporal and spatial trends in parameters for coastal seagrass habitats

Report cards that are designed to monitor environmental trends have the potential to provide a powerful communication tool because they are easy to understand and accessible to the general public, scientists, managers and policy makers. Given this functionality, they are increasingly popular in marine ecosystem reporting. We describe a report card method for seagrass that incorporates spatial and temporal variability in three metrics—meadow area, species and biomass—developed using long-term (greater than 10 years) monitoring data. This framework summarises large amounts of spatially and temporally complex data to give a numeric score that provides reliable comparisons of seagrass condition in both persistent and naturally variable meadows. We provide an example of how this is applied to seagrass meadows in an industrial port in the Great Barrier Reef World Heritage Area of north-eastern Australia

Method for Flavor Tagging in Neutral B Meson Decays

A method is proposed for tagging the flavor of neutral $B$ mesons in the study of CP-violating decay asymmetries. The method makes use of a possible difference in interactions in $B \pi$ or $B^* \pi$ systems with isospins 1/2 and 3/2, and would be particularly clean if the $I = 1/2$ systems can be detected as ``$B^{**}$'' resonances.Comment: Submitted to Phys. Rev. D. 11 pages, LaTeX, Technion-PH-92-40 / PITHA 92/39 / EFI 92-5