Flight capital as a portfolio choice

The authors examine flight capital in the context of portfolio choice. They estimate the stock of flight capital held abroad and compare it with the stock of real (nonfinancial) capital held within each country. For 51 countries they construct estimates (as of 1990) of private domestic capital and flight capital - which combined add up to domestic wealth. There are large regional differences in the proportion of private wealth that is held abroad, ranging from 3 percent in South Asia to 39 percent in Africa. They explain differences in portfolio choice in terms of the capital to labor ratio, indebtedness, exchange rate distortions, and risk ratings - all proxies for differences in the risk-adjusted rate of return on capital. They then apply the results to four policy questions in which private portfolio choices are potentially important: the effect of the East Asian crisis on domestic capital outflows; spillovers; the effect of HIPC debt relief on capital repatriation; and why Africa has so much of its private wealth outside the continent. Their conclusions: 1) The four most severely affected East Asian countries will eventually lose about $250 billion in domestic wealth as a result of the deterioration in risk between March 1997 and September 1998. 2) They found some support for a spillover model. 3) The effect of the HIPC debt relief initiative on capital repatriation will vary massively between HIPC-eligible countries. 4) Africa has by far the lowest capital per worker, which makes massive capital flight from Africa all the more distinctive. Three variables explain capital flight in Africa: exchange rate overvaluation, adverse investor risk ratings, and high indebtedness.Capital Markets and Capital Flows,Economic Theory&Research,International Terrorism&Counterterrorism,Fiscal&Monetary Policy,Banks&Banking Reform,International Terrorism&Counterterrorism,Banks&Banking Reform,Settlement of Investment Disputes,Banking Law,Economic Theory&Research

Transformational strategies: the Margiela Rabbit and the Gecko Girl

Elizabeth Costello, the elderly fiction writer in J.M Coetzee’s novel of the same name, discusses the possibility of how a human being can feel what it is like to be a bat. She believes that to feel thus, one does not need to experience bat life through the sense modalities of being a bat but rather “to be a living bat is to be full of being: being fully a bat is like being fully human, which is also to be full of being” (Coetzee, 2004, p. 69). Elizabeth Costello isn’t interested in clothing but she does believe that to feel what it is like to be a bat one needs the sensations of fullness and embodiedness; the sensation of being a body with limbs that have an extension in space, of being alive to the world. Wearing a dress with more than two sleeves gives me the sense of having more than two arms and in a dress with a tail I have a tail. The feeling of being in certain clothes offers me the potential to “become” something else and to feel expansive. This paper/performance presents findings from the work of two artists and designers who are both using the distinctively cultural form of clothing to explore the human/non-human animal divide. Both artists are putting into practice Deleuzian theories of “becoming other” as a transformational strategy to shift our relationship to our environment and our fellow non- human creatures using clothing, performance, photography and video to do this. The questions we both ask are: in this moment of complexity and uncertainty that the world is currently in, what is the role of imagination in inventing new possible worlds? How can the transformative nature of clothing offer new modes of experience that are possibly more sensual and slower than what we usually give value to and can clothing help to shift our relationship with the environment and other living creatures? Kate Soper argues that if we want to maintain a sustainable world that both humans and non-humans can happily and healthily continue to live in, we need alternative outlets for transcendence” that are not provided by Western industrialist consumerist culture which removes us from a natural simplicity or immanence, rather than returns us to it. (Soper, 1999) Considering these ideas we are interested in attempting to refigure a world where we are the ‘animal’. Two women, possibly wearing tails, will present this paper as a scripted performance

Seagrass communities of the Great Barrier Reef and their desired state: applications for spatial planning and management

The research program reported here evolved from an interest in developing ecologically relevant target criteria that, if met, correspond to desired ecological outcomes (e.g. desired state) for the Great Barrier Reef World Heritage Area (GBRWHA) and to achieving the overarching objective of the Great Barrier Reef Marine Park Authority’s Long-term Sustainability Plan. The objective of the original National Environment Science Program (NESP) Tropical Water Quality Hub (TWQ) Project 3.2.1 Deriving ecologically relevant load targets to meet desired ecosystem condition for the Great Barrier Reef: a case study for seagrass meadows in the Burdekin region was to examine relationships between catchment inputs of sediment and seagrass desired state, and to compare these against the 2018 Water Quality Improvement Plan’s ecological targets. This objective was met using a case study in Cleveland Bay based on sediment loads from the Burdekin River and other smaller catchments that discharge into the bay (Collier et al., 2020). The techniques developed in the Cleveland Bay case study are used in the present report at the scale of the whole GBRWHA for NESP TWQ Hub Project 5.4. To achieve this we followed three steps: (1) a consolidation and verification of seagrass data at the GBRWHA scale, (2) an analysis of the distribution of GBRWHA seagrass habitat and communities, and (3) an estimation of a desired state target for communities with sufficient data. To achieve step 1, we compiled and standardised 35 years of seagrass survey data in a spatial database, including 81,387 georeferenced data points. Twelve seagrass species were recorded, the deepest of which (Halophila spinulosa) was found at 76 m. This database is a valuable resource that provides coastal managers, researchers and the global marine community with a long-term spatial resource describing seagrass populations from the mid1980s against which to benchmark change. For step 2, we identified 88,331 km2 of potential seagrass habitat within the GBRWHA; 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. The environmental conditions that structure the location and extent of these communities included depth, tidal exposure, latitude, current speed, benthic light, proportion of mud, water type, water temperature, salinity, and wind speed. Environmental parameters interact with the topography of the reef and changes in the coastal plain, its watersheds, and its development with latitude. We describe seagrass distributions and communities that are shaped by multiple combinations of these environmental complexities and how that may influence marine spatial planning and environmental protection initiatives (Chapter 3). For step 3, we used more than 20 years of historical data (1995-2018) on seagrass biomass for the diverse seagrass communities of the GBRWHA to develop desired state benchmarks. Of the 36 seagrass communities, desired state was identified for 25 of them, 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 that define community boundaries. We identified a historical, decadal-scale cycle of decline and recovery. Recovery to desired state has occurred for coastal intertidal communities following the most recent declines in 2008 - 2012. A number of the estuarine and coastal subtidal communities have not recovered to desired state biomass in recent years (Chapter 4). This body of work provides a huge step forward in our understanding of the complexities of GBRWHA seagrass communities. We discuss the relevance of these research outputs to future marine spatial planning and management. This includes zoning in “representative areas”, hierarchical monitoring design (e.g. RIMReP), and the setting of ecologically relevant sediment load targets for desired state (e.g. Lambert et al., 2019). The updated seagrass data, seagrass distribution, community classification and desired state targets provides important new information for incorporation into marine spatial planning and management that is discussed in Chapter 5. These applications include: • Future assessments of non-reef habitats within the GBRWHA and GBRMP. • Assessing how risk and spatial protection intersect with seagrass communities and the role they play in protecting seagrass, e.g. Queensland State and Commonwealth marine parks, Fish Habitat Areas, Dugong Protected Areas, Port Exclusion Zones. • Expanding our spatial analysis to areas ecologically connected but outside of the GBRWHA such as Torres Strait, the Gulf of Carpentaria, and Fraser Island coast, where we already have seagrass data. • Designing a hierarchical seagrass monitoring design with coarse scales (intertidal, subtidal, estuary, coast, reef) and fine scales (36 communities). We have identified significant knowledge gaps that should guide future monitoring efforts (e.g. RIMReP and Queensland Land and Sea Ranger Program), including a lack of consistent and recent data for reef seagrass communities. • We identified communities where data is deficient, such as in estuaries where important seagrass communities have potential exposure to multiple threats for which more consistent environmental data would be valuable. • Identifying potential restoration sites. Our work has highlighted the critical role of historical data in understanding spatial complexity and for making informed management decisions on the current state of seagrass in the GBRWHA. Our approach can be adapted for monitoring, management and assessment of pressures at other relevant scales and jurisdictions. Our results guide conservation planning through prioritisation of at-risk communities that are continuing to fail to attain desired state

Subtidal seagrass detector: development of a deep learning seagrass detection and classification model for seagrass presence and density in diverse habitats from underwater photoquadrats

This paper presents the development and evaluation of a Subtidal Seagrass Detector (the Detector). Deep learning models were used to detect most forms of seagrass occurring in a diversity of habitats across the northeast Australian seascape from underwater images and classify them based on how much the cover of seagrass was present. Images were collected by scientists and trained contributors undertaking routine monitoring using drop-cameras mounted over a 50 x 50 cm quadrat. The Detector is composed of three separate models able to perform the specific tasks of: detecting the presence of seagrass (Model #1); classify the seagrass present into three broad cover classes (low, medium, high) (Model #2); and classify the substrate or image complexity (simple of complex) (Model #3). We were able to successfully train the three models to achieve high level accuracies with 97%, 80.7% and 97.9%, respectively. With the ability to further refine and train these models with newly acquired images from different locations and from different sources (e.g. Automated Underwater Vehicles), we are confident that our ability to detect seagrass will improve over time. With this Detector we will be able rapidly assess a large number of images collected by a diversity of contributors, and the data will provide invaluable insights about the extent and condition of subtidal seagrass, particularly in data-poor areas

Light thresholds for seagrasses of the GBRWHA: a synthesis and guiding document

[Extract]. Key Findings. This synthesis contains light thresholds for seagrass species in the Great Barrier Reef World Heritage Area (GBRWHA). The thresholds can be applied to ensure protection of seagrasses from activities that impact water quality and the light environment over the short-term, such as coastal and port developments. Thresholds for long-term maintenance of seagrasses are also proposed. •The synthesis provides clear and consistent guidance on light thresholds to apply in managing potential water quality impacts to seagrass. •All available information on biological light thresholds was tabulated and conservative management thresholds were identified to ensure seagrass protection. •Acute management thresholds are suited to compliance guidelines for managing short-term impacts and these and are the focus of this synthesis. Long-term thresholds are suited to the setting of water quality guidelines for catchment management. •The synthesis identified key areas where further information is required, including: ◦species for which almost no information on light thresholds exists; ◦location and population-specific thresholds particularly for the most at-risk species; ◦definitions of desired state to underpin the development of long-term light guidelines to meet them; ◦the effect of spectral quality on light thresholds; and, consideration of cumulative impacts (temperature, nutrients, sedimentary conditions) on acute and long-term light thresholds. •Light management thresholds for acute impacts are presented for twelve species. Colonising species are the most sensitive to light reduction (i.e. lowest thresholds) and have the shortest time to impact while larger, persistent species have higher light thresholds and a longer time to impact. •The recommended acute management thresholds are ready for application, as the conservative approach (higher light threshold, shortest time to impact) for species with low confidence should ensure protection to seagrass meadows at risk from acute light stress

Developing and refining biological indicators for condition assessments in an integrated monitoring program

[Extract] Indicators representative of ecosystem condition are required for the long-term monitoring of the Great Barrier Reef (GBR) in a Reef Integrated Monitoring and Reporting Program (RIMREP), which tracks progress towards Reef 2050 Plan targets and objectives. Seagrass meadows are highly sensitive to climatic conditions and environmental pressures such as water quality, as seen through recent (past 10 years) changes in abundance in the GBR (McKenzie, et al., 2016). Due to these impacts, GBR seagrass meadows underwent a period of decline from 2009 to 2011. Widespread loss of seagrass occurred, but in 2015 many meadows had started recovering. The storage reserves within seagrass rhizomes were tested for suitability as a complimentary indicator in the MMP/RIMREP because previous studies had suggested that they are good indicators. We set out to test the relationships between total non-structural carbohydrates (TNSC) and seagrass condition (i.e. trend in abundance, either declining pre 2011 or recovering post 2011), seagrass abundance, water temperature and daily light in a temporal analysis using linear models. Samples were collected quarterly from 2008 to 2015 from four locations (8 sites) for three species (917 samples in total) in the Wet Tropics and Burdekin regions. TNSC was significantly (p<0.001) lower pre 2011 during the period of decline (181and 192 mg gDW-1for intertidal sites pooled and subtidal sites pooled, respectively) than post 2011 during recovery (277 and 289 mg gDW-1) for H. uninervis. A similar trend was observed for T. hemprichii, which occurred at intertidal sites only (168 mg gDW-1 in decline and 208 mg gDW-1in recovery), but not for C. serrulata which had the fewest available data points. The differences were even greater when investigating individual sites. TNSC were also correlated (p<0.001) to seagrass abundance during both the decline and recovery phases. TNSC was positively correlated to water temperature, though the period being assessed was relatively mild in terms of temperature extremes. Therefore, light was the main pressure assessed in this project. A direct effect of light limitation (daily light, average of 30 days prior to TNSC collection) on TNSC was not observed, in fact there was a slight negative effect of light in some analyses. This was contrary to our hypothesis, as low light, at least in part, drove declines in seagrass abundance from 2009 –2011. In an additional spatial analysis, differences in TNSC among regions and habitat types were assessed from 39 sites collected in late 2014 across the GBR. This spatial analysis was carried out to explore representativeness of the sites used in the temporal analysis. There was little difference in TNSC among habitats; however, TNSC varied among NRMs and were lowest in the Mackay Whitsunday and Fitzroy NRMs. This exploration of storage reserves, undertaken at a time of dynamic meadow changes, has yielded exciting results on their variation with meadow condition and abundance. However, we did not provide conclusive evidence to support the inclusion of TNSC as an indicator in monitoring programs such as the MMP at this stage, because the link to the main environmental pressure tested –light –was not demonstrated by this analysis. Irrespective of this, TNSC was an indicator of cumulative stress (being correlated to abundance and condition), but the specific pressure(s) could not be identified. This provides justification for further inquiry into the effect of other pressures (e.g. nutrients and flood plume exposure), other biological processes (e.g. reproduction and meadow expansion) and to obtain further data on other species. We also tested the relationship between %cover and biomass, with the aim of developing biomass calibration formulae. Above-ground biomass and %cover was measured in seven mono-specific meadows for four species and four habitat types. Above ground biomass was highly correlated (p<0.001) to % cover, and the correlation was further improved (lower AIC) by factoring canopy height into the calibration. Even after canopy height was included in the calibration, canopy height strongly affected the calibration values and highlighted the importance of habitat/morphology-specific calibration formulae. Further work is required to capture all species and habitat/morphology combinations that are routinely monitored. With further work, these calibration values will enable integration among seagrass monitoring programs including Queensland Ports Seagrass Monitoring Program and GBR historical baseline data

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

Seafloor sediment thickness beneath the VoiLA broad-band ocean-bottom seismometer deployment in the Lesser Antilles from P-to-S delay times

Broad-band ocean-bottom seismometer (OBS) deployments present an opportunity to investigate the seafloor sediment thickness, which is important for constraining sediment deposition, and is also useful for subsequent seismological analyses. The Volatile Recycling in the Lesser Antilles (VoiLA) project deployed 34 OBSs over the island arc, fore- and backarc of the Lesser Antilles subduction zone for 15 months from 2016 to 2017. Using the amplitudes and delay times of P-to-S (Ps) scattered waves from the conversion of teleseismic earthquake Pwaves at the crust–sediment boundary and pre-existing relationships developed for Cascadia, we estimate sediment thickness beneath each OBS. The delay times of the Ps phases vary from 0.20 ± 0.06 to 3.55 ± 0.70 s, generally increasing from north to south. Using a single-sediment and single-crystalline crust earth model in each case, we satisfactorily model the observations of eight OBSs. At these stations we find sediment thicknesses range from 0.43 ± 0.45 to 5.49 ± 3.23 km. To match the observations of nine other OBSs, layered sediment and variable thickness crust is required in the earth model to account for wave interference effects on the observed arrivals. We perform an inversion with a two-layer sediment and a single-layer crystalline crust in these locations finding overall sediment thicknesses of 1.75 km (confidence region: 1.45–2.02 km) to 7.93 km (confidence region: 6.32–11.05 km), generally thinner than the initial estimates based on the pre-existing relationships. We find agreement between our modelled velocity structure and the velocity structure determined from the VoiLA active-source seismic refraction experiment at the three common locations. Using the Ps values and estimates from the VoiLA refraction experiment, we provide an adjusted relationship between delay time and sediment equations for the Lesser Antilles. Our new relationship is H=1.42dt$^{1.44}$ , where H is sediment thickness in kilometres and dt is mean observed Ps delay time in seconds, which may be of use in other subduction zone settings with thick seafloor sediments