A geospatial appraisal of ecological and geomorphic change on Diego Garcia Atoll, Chagos Islands (British Indian OceanTerritory)

This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This study compiled a wide range of modern and historic geospatial datasets to examine ecological and geomorphic change at Diego Garcia Atoll across a 38-year period (1967–2005). This remarkable collection of spatially referenced information offered an opportunity to advance our understanding of the nature and extent of environmental change that has taken place with the construction of the military airbase at Diego Garcia. Changes assessed included movements of the lagoon rim shorelines, changes in the terrestrial vegetation on the lagoon rim and amendments to the bathymetry of the lagoon basin through dredging activities. Data compiled included detailed shoreline and vegetation maps produced as part of the H.M.S. Vidal Indian Ocean Expedition (1967), three Ikonos satellite images acquired in 2005 that collectively covered the complete Atoll area, a ground truthing field dataset collected in the northern section of the lagoon for the purpose of seafloor mapping (2005), observational evidence of shoreline erosion including photographs and descriptions of seawater inundations and bathymetric soundings from five independent surveys of the lagoon floor (1967, 1985, 1987, 1988 and 1997). Results indicated that much of the change along the lagoon rim is associated with the expansion of the inner lagoon shoreline as a result of the construction of the military airbase, with an estimated increase in land area of 3.01 km2 in this portion of the atoll rim. Comparisons of 69 rim width transects measured from 1967 and 2005 indicated that shorelines are both eroding (26 transects) and accreting (43 transects). Within a total vegetated area of 24 km2, there was a notable transition from Cocos Woodland to Broadleaf Woodland for a land area of 5.6 km2. From the hydrographic surveys, it was estimated that approximately 0.55 km3 of carbonate sediment material has been removed from the northwest quadrant of the lagoon, particularly in the vicinity of the Main Passage. As no previous record of benthic character exists, a complete benthic habitat map of the atoll was derived through classification of the three IKONOS satellite images. Management implications arising from this overall appraisal of geomorphic and ecological change at Diego Garcia included the need for ongoing monitoring of shoreline change at a representative set of sites around the atoll rim, monitoring of the water flow regime through the northern channels between the open ocean and the lagoon basin and an ongoing mapping campaign to record periodic changes in the character of the benthic surface ecology.BLUE Marine Foundatio

Reef-scale assessment of intertidal large benthic foraminifera populations on one tree Island, great barrier reef and their future carbonate production potential in a warming ocean

Populations of large benthic foraminiferans (LBFs) that inhabit coral reef platforms are major producers of calcium carbonate (CaCO3) in reef ecosystems. This study documented the population density of living intertidal LBF populations at One Tree Reef (OTR), southern Great Barrier Reef, in a community dominated by Marginopora vertebralis and Baculogypsina sphaerulata. Densities of 7.7 × 103 M. vertebralis individuals (ind.)/m2 and 4.5 × 105 B. sphaerulata ind./m2 were estimated for these populations in May 2011. We applied remote-sensing technology to determine reef-scale estimates of suitable Foraminifera habitats and used these to estimate overall stocks of LBF populations on the intertidal algal flat at OTR of ca. 2800 metric tons. The growth rate of M. vertebralis was determined in a laboratory study, and the data were used to calculate the annual CaCO3 production of the reef flat by the LBF population. The response of M. vertebralis to ocean warming was investigated using 3-week incubations at temperatures ranging from ambient sea surface temperature to +6°C. There were significant decreases in growth and concomitant CaCO3 production in 6°C warmer water, which resulted in shell dissolution of M. vertebralis. These results indicate that climate-driven ocean warming projected for the region will result in significant decreases in CaCO3 production in overall foraminiferan populations, although species-specific effects should be further investigated

Chapter 2 ‘A CLOSE AND FRIENDLY ALLIANCE’: BIOLOGY, GEOLOGY AND THE GREAT BARRIER REEF EXPEDITION OF 1928–1929

oceanography, climate change, reefs, marine science, marine conservation, marine researc

Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches

We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected

Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches

We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected

Predicting Responses of Geo-ecological Carbonate Reef Systems to Climate Change: A Conceptual Model and Review

[Chapter Abstract] 230Coral reefs provide critical ecological and geomorphic (e.g. sediment production for reef-fronted shoreline maintenance) services, which interact in complex and dynamic ways. These services are under threat from climate change, requiring dynamic modelling approaches that predict how reef systems will respond to different future climate scenarios. Carbonate budgets, which estimate net reef calcium carbonate production, provide a comprehensive ‘snap-shot’ assessment of reef accretionary potential and reef stability. These budgets, however, were not intended to account for the full suite of processes that maintain coral reef services or to provide predictive capacity on longer timescales (decadal to centennial). To respond to the dual challenges of enhancing carbonate budget assessments and advancing their predictive capacity, we applied a novel model elicitation and review method to create a qualitative geo-ecological carbonate reef system model that links geomorphic, ecological and physical processes. Our approach conceptualizes relationships between net carbonate production, sediment transport and landform stability, and rates knowledge confidence to reveal major knowledge gaps and critical future research pathways. The model provides a blueprint for future coral reef research that aims to quantify net carbonate production and sediment dynamics, improving our capacity to predict responses of reefs and reef-fronted shorelines to future climate change.https://nsuworks.nova.edu/occ_facbooks/1116/thumbnail.jp

Chapter 4 PREDICTING RESPONSES OF GEO-ECOLOGICAL CARBONATE REEF SYSTEMS TO CLIMATE CHANGE: A CONCEPTUAL MODEL AND REVIEW

oceanography, climate change, reefs, marine science, marine conservation, marine researc

Mapping coral reef environments: A review of historical methods, recent advances and future opportunities

Coral reef environments support high levels of marine biodiversity, they are important sites for coastal habitation and they provide a range of goods and ecosystem services such as nearshore fisheries, economic revenue from tourism and breeding sites for seabirds and turtles. Mapping is a fundamental activity that underpins our understanding of coral reef environments and helps to shape policies in resource management and conservation. This is particularly the case for quantifying the area of landcover types associated with reef environments, including coral patches, seagrasses and mangroves, but also for monitoring how these change over time and modelling how spatial patterns apparent on reefs are related to environmental drivers. Field techniques and aerial photography have historically played a crucial role in mapping coral reef environments, which has recently seen a transition toward the processing of satellite remote sensing images. This paper examines a series of maps produced of Low Isles, the most mapped island on the Great Barrier Reef, to review historical methods for mapping coral reefs because of the critical importance of understanding how past maps were made, which determines appropriate uses to which they can be put. Recent advances and future opportunities for the application of mapping technologies to coral reefs are also evaluated, including the use of unmanned aerial vehicle (UAV) platforms for airborne surveys, delivery of information through web-based platforms and improvements in the quality of information for making and presenting maps. Maps have transformed the way we have responded to both historic and contemporary coral reef problems. This timely review communicates how maps, and the fast growing technologies that are employed to produce them, are central to our understanding of coral reef environments. Recent advances that may drive exciting new environmental management tools are identified

Critical cartography and the use of new technologies for conserving the Australian coastline: a case study from Lord Howe Island

Maps exert power. In this paper I explore the power of maps in relation to the technical methods employed and the political context of their production. The internal power of maps is realised in the actions taken by cartographers themselves when making maps, while the external power of maps is both realised by the patrons of cartography and wielded through the use of cartographic products as agents for natural resource management, in particular for defining conservation strategies. An Australian case study of coastal mapping is used to examine the methods employed and motivation behind map production through a series of recent remote sensing initiatives to map Lord Howe Island, New South Wales. Through this case study I explore the subjectivities associated with the placement of boundaries in the scientific practice of cartography. I argue that a new epistemological reading of maps is necessary, as sources of information on socio-politically constructed worlds as much as the phenomenological world of objects. Such a reading is particularly important given recent advances in technologies, such as remote sensing, that are increasingly used to inform coastal management, and which propagate in profound new ways the power of maps

Will coral islands maintain their growth over the next century? A deterministic model of sediment availability at Lady Elliot Island, Great Barrier Reef

A geomorphic assessment of reef system calcification is conducted for past (3200 Ka to present), present and future (2010-2100) time periods. Reef platform sediment production is estimated at 569 m3 yr−1 using rate laws that express gross community carbonate production as a function of seawater aragonite saturation, community composition and rugosity and incorporating estimates of carbonate removal from the reef system. Key carbonate producers including hard coral, crustose coralline algae and Halimeda are mapped accurately (mean R2 = 0.81). Community net production estimates correspond closely to independent census-based estimates made in-situ (R2 = 0.86). Reef-scale outputs are compared with historic rates of production generated from (i) radiocarbon evidence of island deposition initiation around 3200 years ago, and (ii) island volume calculated from a high resolution island digital elevation model. Contemporary carbonate production rates appear to be remarkably similar to historical values of 573 m3 yr−1. Anticipated future seawater chemistry parameters associated with an RCP8.5 emissions scenario are employed to model rates of net community calcification for the period 2000-2100 on the basis of an inorganic aragonite precipitation law, under the assumption of constant benthic community character. Simulations indicate that carbonate production will decrease linearly to a level of 118 m3 yr−1 by 2100 and that by 2150 aragonite saturation levels may no longer support the positive budgetary status necessary to sustain island accretion. Novel aspects of this assessment include the development of rate law parameters to realistically represent the variable composition of coral reef benthic carbonate producers, incorporation of three dimensional rugosity of the entire reef platform and the coupling of model outputs with both historical radiocarbon dating evidence and forward hydrochemical projections to conduct an assessment of island evolution through time. By combining several lines of evidence in a deterministic manner, an assessment of changes in carbonate production is carried out that has tangible geomorphic implications for sediment availability and associated island evolution