ORCID Profile
0000-0002-4008-3053
Current Organisation
James Cook University
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Environmental Science and Management | Conservation and Biodiversity | Environmental Management | Marine and Estuarine Ecology (incl. Marine Ichthyology) | Ecosystem Function | Freshwater Ecology
Ecosystem Assessment and Management at Regional or Larger Scales | Ecosystem Assessment and Management of Coastal and Estuarine Environments | Ecosystem Assessment and Management of Fresh, Ground and Surface Water Environments | Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Flora, Fauna and Biodiversity at Regional or Larger Scales | Ecosystem Assessment and Management of Mountain and High Country Environments |
Publisher: Springer Science and Business Media LLC
Date: 06-09-2022
DOI: 10.1038/S41597-022-01635-5
Abstract: Assessments of the status of tidal flats, one of the most extensive coastal ecosystems, have been h ered by a lack of data on their global distribution and change. Here we present globally consistent, spatially-explicit data of the occurrence of tidal flats, defined as sand, rock or mud flats that undergo regular tidal inundation. More than 1.3 million Landsat images were processed to 54 composite metrics for twelve 3-year periods, spanning four decades (1984–1986 to 2017–2019). The composite metrics were used as predictor variables in a machine-learning classification trained with more than 10,000 globally distributed training s les. We assessed accuracy of the classification with 1,348 stratified random s les across the mapped area, which indicated overall map accuracies of 82.2% (80.0–84.3%, 95% confidence interval) and 86.1% (84.2–86.8%, 95% CI) for version 1.1 and 1.2 of the data, respectively. We expect these maps will provide a means to measure and monitor a range of processes that are affecting coastal ecosystems, including the impacts of human population growth and sea level rise.
Publisher: Wiley
Date: 10-01-2018
DOI: 10.1002/FEE.1747
Publisher: Wiley
Date: 10-08-2017
DOI: 10.1002/RSE2.59
Publisher: Springer Science and Business Media LLC
Date: 08-02-2023
Publisher: Wiley
Date: 17-11-2017
DOI: 10.1111/ECOG.02957
Publisher: Springer Science and Business Media LLC
Date: 16-08-2021
Publisher: Cold Spring Harbor Laboratory
Date: 11-2017
DOI: 10.1101/212464
Abstract: Recent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to make ecosystem maps from remote sensing data. We have developed a free and open-access online remote sensing and environmental modelling application, REMAP ( the remote ecosystem monitoring and assessment pipeline remap-app.org ) that enables volunteers, managers, and scientists with little or no experience in remote sensing to develop high-resolution classified maps of land cover and land use change over time. REMAP utilizes the geospatial data storage and analysis capacity of the Google Earth Engine, and requires only spatially resolved training data that define map classes of interest (e.g., ecosystem types). The training data, which can be uploaded or annotated interactively within REMAP, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in REMAP represent topographic (e.g. slope, elevation), spectral (Landsat Archive image composites) and climatic variables (precipitation, temperature) that can inform on the distribution of ecosystems and land cover classes. The ability of REMAP to develop and export high-quality classified maps in a very short ( minute) time frame represents a considerable advance towards globally accessible and free application of remote sensing technology. By enabling access to data and simplifying remote sensing classifications, REMAP can catalyse the monitoring of land use and change to support environmental conservation, including developing inventories of bio ersity, identifying hotspots of ecosystem ersity, ecosystem-based spatial conservation planning, mapping ecosystem loss at local scales, and supporting environmental education initiatives.
Publisher: Wiley
Date: 05-07-2018
Publisher: Cold Spring Harbor Laboratory
Date: 26-03-2020
DOI: 10.1101/2020.03.25.008110
Abstract: Measuring forest degradation is important for understanding and designing measures to protect bio ersity and the capacity of forests to deliver ecosystem services. Conservation planning, particularly the prioritization of management interventions for forests, is often lacking spatial data on ecological condition, and it is often overlooked within decision-making processes. Existing methods for assessing forest degradation via proxies or binary measures (i.e. intact or not) cannot adequately consider the important variations of ecological condition. Direct methods to measure degradation (e.g. through remote sensing) require extensive training data, calibration and validation, and may be too sensitive to small-scale or short-term changes which may not be related to degradation. We developed a metric termed Forest Condition (FC) which aims to measure the degree of forest degradation, incorporating temporal history of forest change over a large spatial extent. We parameterized this metric based on estimated changes in above ground biomass in the context of forest fragmentation over time to estimate a continuous measure of forest degradation for Congo Basin countries. We estimate that just less than 70% of Congo Basin forests remain fully intact. FC was validated by direct remote sensing measurements from Landsat imagery for DRC. Results showed that FC was significantly positively correlated with forest canopy cover, gap area per hectare, and magnitude of temporal change in Normalized Burn Ratio. We tested the ability of FC to distinguish primary and secondary degradation and deforestation and found significant differences in gap area and spectral anomalies to validate our theoretical model. We used the IUCN Red List of Ecosystems criteria to demonstrate the value of applying forest degradation to assess the risk of ecosystem collapse. Based on this assessment, we found that without including FC in the assessment of biotic disruption, 12 ecosystems could not have a threat status assigned, and a further 9 ecosystems would have a lower threat status. Our overall assessment of ecosystems found approximately half of forest of Congo Basin ecosystem types which cover over 20% of all forest area are threatened including 4 ecosystems ( % of total area) which are critically engendered. FC is a transferrable and scalable assessment to support forest monitoring, planning, and management.
Publisher: Wiley
Date: 20-11-2018
DOI: 10.1111/DDI.12675
Publisher: Wiley
Date: 07-01-2015
DOI: 10.1111/AEC.12211
Publisher: Wiley
Date: 31-01-2019
DOI: 10.1111/ECOG.04143
Publisher: American Association for the Advancement of Science (AAAS)
Date: 13-05-2022
Abstract: Tidal wetlands are expected to respond dynamically to global environmental change, but the extent to which wetland losses have been offset by gains remains poorly understood. We developed a global analysis of satellite data to simultaneously monitor change in three highly interconnected intertidal ecosystem types-tidal flats, tidal marshes, and mangroves-from 1999 to 2019. Globally, 13,700 square kilometers of tidal wetlands have been lost, but these have been substantially offset by gains of 9700 km
Publisher: MDPI AG
Date: 15-11-2022
DOI: 10.3390/RS14225766
Abstract: Estimating the distribution, extent and change of coastal ecosystems is essential for monitoring global change. However, spatial models developed to estimate the distribution of land cover types require accurate and up-to-date reference data to support model development, model training and data validations. Owing to the labor-intensive tasks required to develop reference datasets, often requiring intensive c aigns of image interpretation and/or field work, the availability of sufficiently large quality and well distributed reference datasets has emerged as a major bottleneck hindering advances in the field of continental to global-scale ecosystem mapping. To enhance our ability to model coastal ecosystem distributions globally, we developed a global reference dataset of 193,105 occurrence records of seven coastal ecosystem types—muddy shorelines, mangroves, coral reefs, coastal saltmarshes, seagrass meadows, rocky shoreline, and kelp forests—suitable for supporting current and next-generation remote sensing classification models. coastTrain version 1.0 contains curated occurrence records collected by several global mapping initiatives, including the Allen Coral Atlas, Global Tidal Flats, Global Mangrove Watch and Global Tidal Wetlands Change. To facilitate use and support consistency across studies, coastTrain has been harmonized to the International Union for the Conservation of Nature’s (IUCN) Global Ecosystem Typology. coastTrain is an ongoing collaborative initiative designed to support sharing of reference data for coastal ecosystems, and is expected to support novel global mapping initiatives, promote validations of independently developed data products and to enable improved monitoring of rapidly changing coastal environments worldwide.
Publisher: Wiley
Date: 05-2015
DOI: 10.1111/CONL.12167
Publisher: The Royal Society
Date: 20-09-2017
Abstract: Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment.
Publisher: Wiley
Date: 14-05-2019
Publisher: Wiley
Date: 15-12-2023
DOI: 10.1111/COBI.14031
Abstract: Bio ersity offsets aim to counterbalance the residual impacts of development on species and ecosystems. Guidance documents explicitly recommend that bio ersity offset actions be located close to the location of impact because of higher potential for similar ecological conditions, but allowing greater spatial flexibility has been proposed. We examined the circumstances under which offsets distant from the impact location could be more likely to achieve no net loss or provide better ecological outcomes than offsets close to the impact area. We applied a graphical model for migratory shorebirds in the East Asian–Australasian Flyway as a case study to explore the problems that arise when incorporating spatial flexibility into offset planning. Spatially flexible offsets may alleviate impacts more effectively than local offsets however, the risks involved can be substantial. For our case study, there were inadequate data to make robust conclusions about the effectiveness and equivalence of distant habitat‐based offsets for migratory shorebirds. Decisions around offset placement should be driven by the potential to achieve equivalent ecological outcomes however, when considering more distant offsets, there is a need to evaluate the likely increased risks alongside the potential benefits. Although spatially flexible offsets have the potential to provide more cost‐effective bio ersity outcomes and more cobenefits, our case study showed the difficulty of demonstrating these benefits in practice and the potential risks that need to be considered to ensure effective offset placement.
Publisher: Elsevier BV
Date: 03-2021
Publisher: Wiley
Date: 10-05-2023
Abstract: pH dependence on water soluble aggregates is well‐known in the field of low molecular weight gelators (LMWGs), with different aggregates sometimes having very different properties depending on their final pH. This aggregation determines their applications and performance. Here, we investigate the pH dependence of perylene bisimide gels initially solutions are formed at a high pH and gels form as the pH is decreased. We find it is not only the final pH but also the starting pH that can impact the resulting gel. We use small angle neutron scattering (SANS), rheology, 1 H NMR spectroscopy and absorption spectroscopy to examine the effect of starting pH on gelation kinetics and final gel properties. Adjusting the solution from pH 9 (where there are few or no aggregates) to pH 6 results in the formation of different worm‐like micelles than the ones directly formed at pH 6, leading to again gels with different mechanical properties. This work highlights the importance of controlling the pH of solutions before gelation, but also opens up more possible morphologies and therefore more properties from the same molecule.
Publisher: Springer Science and Business Media LLC
Date: 12-10-2022
DOI: 10.1038/S41586-022-05318-4
Abstract: As the United Nations develops a post-2020 global bio ersity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of ‘living in harmony with nature’ 1,2 . Advancing dual imperatives to conserve bio ersity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management 3 . Ecosystems vary in their biota 4 , service provision 5 and relative exposure to risks 6 , yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This h ers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth’s ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global bio ersity framework.
Publisher: Informa UK Limited
Date: 06-2016
DOI: 10.1071/MU15046
Publisher: The Royal Society
Date: 22-06-2013
Abstract: Sea-level rise (SLR) will greatly alter littoral ecosystems, causing habitat change and loss for coastal species. Habitat loss is widely used as a measurement of the risk of extinction, but because many coastal species are migratory, the impact of habitat loss will depend not only on its extent, but also on where it occurs. Here, we develop a novel graph-theoretic approach to measure the vulnerability of a migratory network to the impact of habitat loss from SLR based on population flow through the network. We show that reductions in population flow far exceed the proportion of habitat lost for 10 long-distance migrant shorebirds using the East Asian–Australasian Flyway. We estimate that SLR will inundate 23–40% of intertidal habitat area along their migration routes, but cause a reduction in population flow of up to 72 per cent across the taxa. This magnifying effect was particularly strong for taxa whose migration routes contain bottlenecks—sites through which a large fraction of the population travels. We develop the bottleneck index , a new network metric that positively correlates with the predicted impacts of habitat loss on overall population flow. Our results indicate that migratory species are at greater risk than previously realized.
Publisher: Wiley
Date: 04-07-2018
DOI: 10.1111/COBI.13107
Abstract: Ongoing ecosystem degradation and transformation are major threats to bio ersity. Measuring ecosystem change toward collapse relies on monitoring indicators that quantify key ecological processes. Yet little guidance is available on selection and use of indicators for ecosystem risk assessment. We reviewed indicator use in ecological studies of ecosystem collapse in marine pelagic and temperate forest ecosystems. We examined indicator-selection methods, indicator types (geographic distribution, abiotic, biotic), methods of assessing multiple indicators, and temporal quality of time series. We compared how these factors were applied in the ecological studies with how they were applied in risk assessments by using the International Union for Conservation of Nature's Red List of Ecosystems (RLE), for which indicators are used to estimate risk of ecosystem collapse. Ecological studies and RLE assessments rarely reported how indicators were selected, particularly in terrestrial ecosystems. Few ecological studies and RLE assessments quantified ecosystem change based on all 3 indicator types, and indicators types used differed between marine and terrestrial ecosystems. Several studies used indices or multivariate analyses to assess multiple indicators simultaneously, but RLE assessments did not because as RLE guidelines advise against them. Most studies and RLE assessments used time-series data that spanned at least 30 years, which increases the probability of reliably detecting change. Limited use of indicator-selection protocols and infrequent use of all 3 indicator types may h er accurate detection of change. To improve the value of risk assessments for informing policy and management, we recommend using explicit protocols, including conceptual models, to identify and select indicators a range of indicators spanning distributional, abiotic, and biotic features indices and multivariate analyses with extreme care until guidelines are developed time series with sufficient data to increase ability to accurately diagnose directional change data from multiple sources to support assessments and explicitly reporting steps in the assessment process.
Publisher: Wiley
Date: 24-01-2019
DOI: 10.1111/DDI.12884
Publisher: Springer Science and Business Media LLC
Date: 30-08-2023
DOI: 10.1038/S41586-023-06448-Z
Abstract: Several coastal ecosystems—most notably mangroves and tidal marshes—exhibit biogenic feedbacks that are facilitating adjustment to relative sea-level rise (RSLR), including the sequestration of carbon and the trapping of mineral sediment 1 . The stability of reef-top habitats under RSLR is similarly linked to reef-derived sediment accumulation and the vertical accretion of protective coral reefs 2 . The persistence of these ecosystems under high rates of RSLR is contested 3 . Here we show that the probability of vertical adjustment to RSLR inferred from palaeo-stratigraphic observations aligns with contemporary in situ survey measurements. A deficit between tidal marsh and mangrove adjustment and RSLR is likely at 4 mm yr −1 and highly likely at 7 mm yr −1 of RSLR. As rates of RSLR exceed 7 mm yr −1 , the probability that reef islands destabilize through increased shoreline erosion and wave over-topping increases. Increased global warming from 1.5 °C to 2.0 °C would double the area of mapped tidal marsh exposed to 4 mm yr −1 of RSLR by between 2080 and 2100. With 3 °C of warming, nearly all the world’s mangrove forests and coral reef islands and almost 40% of mapped tidal marshes are estimated to be exposed to RSLR of at least 7 mm yr −1 . Meeting the Paris agreement targets would minimize disruption to coastal ecosystems.
Publisher: Springer Science and Business Media LLC
Date: 31-08-2021
Publisher: Springer Science and Business Media LLC
Date: 13-04-2017
DOI: 10.1038/NCOMMS14895
Abstract: Migratory animals are threatened by human-induced global change. However, little is known about how stopover habitat, essential for refuelling during migration, affects the population dynamics of migratory species. Using 20 years of continent-wide citizen science data, we assess population trends of ten shorebird taxa that refuel on Yellow Sea tidal mudflats, a threatened ecosystem that has shrunk by % in recent decades. Seven of the taxa declined at rates of up to 8% per year. Taxa with the greatest reliance on the Yellow Sea as a stopover site showed the greatest declines, whereas those that stop primarily in other regions had slowly declining or stable populations. Decline rate was unaffected by shared evolutionary history among taxa and was not predicted by migration distance, breeding range size, non-breeding location, generation time or body size. These results suggest that changes in stopover habitat can severely limit migratory populations.
Publisher: Cold Spring Harbor Laboratory
Date: 20-08-2020
DOI: 10.1101/2020.08.18.256750
Abstract: Myanmar is highly bio erse, with more than 16,000 plant, 314 mammal, 1131 bird, 293 reptile, and 139 hibian species. Supporting this bio ersity is a variety of natural ecosystems—mostly undescribed—including tropical and subtropical forests, savannas, seasonally inundated wetlands, extensive shoreline and tidal systems, and alpine ecosystems. Although Myanmar contains some of the largest intact natural ecosystems in Southeast Asia, remaining ecosystems are under threat from accelerating land use intensification and over-exploitation. In this period of rapid change, a systematic risk assessment is urgently needed to estimate the extent and magnitude of human impacts and identify ecosystems most at risk to help guide strategic conservation action. Here we provide the first comprehensive conservation assessment of Myanmar’s natural terrestrial ecosystems using the IUCN Red List of Ecosystems categories and criteria. We identified 64 ecosystem types for the assessment, and used models of ecosystem distributions and syntheses of existing data to estimate declines in distribution, range size, and functioning of each ecosystem. We found that more than a third (36.9%) of Myanmar’s area has been converted to anthropogenic ecosystems over the last 2-3 centuries, leaving nearly half of Myanmar’s ecosystems threatened (29 of 64 ecosystems). A quarter of Myanmar’s ecosystems were identified as Data Deficient, reflecting a paucity of studies and an urgency for future research. Our results show that, with nearly two-thirds of Myanmar still covered in natural ecosystems, there is a crucial opportunity to develop a comprehensive protected area network that sufficiently represents Myanmar’s terrestrial ecosystem ersity.
Publisher: Springer Science and Business Media LLC
Date: 20-01-2021
DOI: 10.1038/S41467-021-20999-7
Abstract: A Correction to this paper has been published: 0.1038/s41467-021-20999-7.
Publisher: The Royal Society
Date: 19-02-2015
Abstract: The newly developed IUCN Red List of Ecosystems is part of a growing toolbox for assessing risks to bio ersity, which addresses ecosystems and their functioning. The Red List of Ecosystems standard allows systematic assessment of all freshwater, marine, terrestrial and subterranean ecosystem types in terms of their global risk of collapse. In addition, the Red List of Ecosystems categories and criteria provide a technical base for assessments of ecosystem status at the regional, national, or subnational level. While the Red List of Ecosystems criteria were designed to be widely applicable by scientists and practitioners, guidelines are needed to ensure they are implemented in a standardized manner to reduce epistemic uncertainties and allow robust comparisons among ecosystems and over time. We review the intended application of the Red List of Ecosystems assessment process, summarize ‘best-practice’ methods for ecosystem assessments and outline approaches to ensure operational rigour of assessments. The Red List of Ecosystems will inform priority setting for ecosystem types worldwide, and strengthen capacity to report on progress towards the Aichi Targets of the Convention on Biological Diversity. When integrated with other IUCN knowledge products, such as the World Database of Protected Areas/Protected Planet, Key Bio ersity Areas and the IUCN Red List of Threatened Species, the Red List of Ecosystems will contribute to providing the most complete global measure of the status of bio ersity yet achieved.
Publisher: Wiley
Date: 08-05-2014
DOI: 10.1890/130260
Publisher: MDPI AG
Date: 09-11-2012
DOI: 10.3390/RS4113417
Publisher: Wiley
Date: 20-02-2017
DOI: 10.1111/COBI.12988
Abstract: Assessments of risk to bio ersity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species' extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1-1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer-scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid-measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape-scale threats to species and ecosystems.
Publisher: Wiley
Date: 21-01-2021
DOI: 10.1111/COBI.13638
Abstract: Tidal flats are a globally distributed coastal ecosystem important for supporting bio ersity and ecosystem services. Local to continental‐scale studies have documented rapid loss of tidal habitat driven by human impacts, but assessments of progress in their conservation are lacking. With an internally consistent estimate of distribution and change, based on Landsat satellite imagery, now available for the world's tidal flats, we examined tidal flat representation in protected areas (PAs) and human pressure on tidal flats. We determined tidal flat representation and its net change in PAs by spatially overlaying tidal flat maps with the World Database of Protected Areas. Similarly, we overlaid the most recent distribution map of tidal flats (2014–2016) with the human modification map (HM c ) (range from 0, no human pressure, to 1, very high human pressure) to estimate the human pressure exerted on this ecosystem. Sixty‐eight percent of the current extent of tidal flats is subject to moderate to very high human pressure (HM c 0.1), but 31% of tidal flat extent occurred in PAs, far exceeding PA coverage of the marine (6%) and terrestrial (13%) realms. Net change of tidal flat extent inside PAs was similar to tidal flat net change outside PAs from 1999 to 2016. Substantial shortfalls in protection of tidal flats occurred across Asia, where large intertidal extents coincided with high to very high human pressure (HM c 0.4–1.0) and net tidal flat losses up to 86.4 km² (95% CI 83.9–89.0) occurred inside in idual PAs in the study period. Taken together, our results show substantial progress in PA designation for tidal flats globally, but that PA status alone does not prevent all habitat loss. Safeguarding the world's tidal flats will thus require deeper understanding of the factors that govern their dynamics and effective policy that promotes holistic coastal and catchment management strategies.
Publisher: Wiley
Date: 17-01-2017
DOI: 10.1111/DDI.12533
Publisher: Informa UK Limited
Date: 06-2016
DOI: 10.1071/MU15056
Publisher: Elsevier BV
Date: 06-2021
Publisher: Wiley
Date: 08-06-2022
DOI: 10.1111/COBI.13905
Abstract: Coastal wetlands around the world have been degraded by human activities. Global declines in the extent of important coastal wetlands, including mangroves, salt marshes, and tidal flats, necessitate mitigation and restoration efforts. However, some well‐meaning management actions, particularly mangrove afforestation, can inadvertently cause further loss and degradation of other habitats if these actions are not planned carefully. In particular, there is a potential conflict between mangrove and shorebird conservation because mangrove afforestation and restoration may occur at the expense of bare tidal flats, which form the main foraging habitats for threatened shorebirds and support other coastal organisms. We examined several case studies that illustrate the trade‐off between mangrove restoration and bare tidal flat maintenance. To investigate whether these ex les reflect an emerging broad‐scale problem, we used satellite imagery to quantify the change in mangrove habitat extent in 22 important shorebird areas in mainland China from 2000 to 2015.The extent of tidal flat across all sites declined significantly ( p 0.01, n = 22) while among sites with mangroves present, the extent of mangroves expanded significantly ( p 0.01, n = 14). Our results suggest mangrove expansion and tidal flat loss have considerably reduced shorebird habitat in 8 of these sites. To improve the overall conservation outcome, we devised a decision tree for addressing the dilemma. Important factors to consider include whether the area of interest is of importance to shorebirds and what the potential impacts of mangrove expansion are what the value of the proposed mangrove ecosystem is compared with the existing ecosystem and that a conflict‐resolution process will be needed if the choices are very similar. With careful consideration of alternative management strategies, decision makers can ensure that the conservation of mangroves does not imperil migratory shorebirds.
Publisher: Wiley
Date: 03-2015
DOI: 10.1890/140022
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.JENVMAN.2018.10.057
Abstract: Wetland restoration is a major objective of environmental management worldwide. We present a frameworkat the regional level that prioritizes historical bio ersity and restoration suitability. The goal of the framework is to maximize bio ersity gains from restoration while minimizing the cost. We used C-Plan, a prioritization tool for systematic conservation planning (SCP), to balance the bio ersity gains withthe costs of restoration, or restoration suitability. We overlaid historical spatial data from 1995 to estimate historical distributions of 91 bio ersity features. These features were used to conduct an irreplaceability analysis to assess the restoration value of historical bio ersity. We then modelled restoration suitability based on environmental data of six criteria. Finally, we applied a complementarity analysis to achieve the quantitative targets of all bio ersity features while minimizing the cost of restoration. We tested this framework in the highly degraded wetlands ofSanjiang Plain, China. By applying our framework to Sanjiang Plain, we successfully identified areas with both high restoration value and high restoration suitability. The area of this cost-effective plan was an extension of 4620 km
Publisher: Springer Science and Business Media LLC
Date: 02-08-2021
DOI: 10.1038/S41597-021-00958-Z
Abstract: Coral reef management and conservation stand to benefit from improved high-resolution global mapping. Yet classifications underpinning large-scale reef mapping to date are typically poorly defined, not shared or region-specific, limiting end-users’ ability to interpret outputs. Here we present Reef Cover , a coral reef geomorphic zone classification, developed to support both producers and end-users of global-scale coral reef habitat maps, in a transparent and version-based framework. Scalable classes were created by focusing on attributes that can be observed remotely, but whose membership rules also reflect deep knowledge of reef form and functioning. Bridging the ide between earth observation data and geo-ecological knowledge of reefs, Reef Cover maximises the trade-off between applicability at global scales, and relevance and accuracy at local scales. Two case studies demonstrate application of the Reef Cover classification scheme and its scientific and conservation benefits: 1) detailed mapping of the Cairns Management Region of the Great Barrier Reef to support management and 2) mapping of the Caroline and Mariana Island chains in the Pacific for conservation purposes.
Publisher: Springer Science and Business Media LLC
Date: 19-12-2019
DOI: 10.1038/S41586-018-0805-8
Abstract: Increasing human populations around the global coastline have caused extensive loss, degradation and fragmentation of coastal ecosystems, threatening the delivery of important ecosystem services
Publisher: MDPI AG
Date: 30-07-2022
DOI: 10.3390/RS14153657
Abstract: Mangroves are a globally important ecosystem that provides a wide range of ecosystem system services, such as carbon capture and storage, coastal protection and fisheries enhancement. Mangroves have significantly reduced in global extent over the last 50 years, primarily as a result of deforestation caused by the expansion of agriculture and aquaculture in coastal environments. However, a limited number of studies have attempted to estimate changes in global mangrove extent, particularly into the 1990s, despite much of the loss in mangrove extent occurring pre-2000. This study has used L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA) for 11 epochs from 1996 to 2020 to develop a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. This approach was applied between all image-date pairs producing 10 maps for each epoch, which were summarised to produce the global mangrove time-series. The resulting mangrove extent maps had an estimated accuracy of 87.4% (95th conf. int.: 86.2–88.6%), although the accuracies of the in idual gain and loss change classes were lower at 58.1% (52.4–63.9%) and 60.6% (56.1–64.8%), respectively. Sources of error included misregistration in the SAR mosaic datasets, which could only be partially corrected for, but also confusion in fragmented areas of mangroves, such as around aquaculture ponds. Overall, 152,604 km2 (133,996–176,910) of mangroves were identified for 1996, with this decreasing by −5245 km2 (−13,587–1444) resulting in a total extent of 147,359 km2 (127,925–168,895) in 2020, and representing an estimated loss of 3.4% over the 24-year time period. The Global Mangrove Watch Version 3.0 represents the most comprehensive record of global mangrove change achieved to date and is expected to support a wide range of activities, including the ongoing monitoring of the global coastal environment, defining and assessments of progress toward conservation targets, protected area planning and risk assessments of mangrove ecosystems worldwide.
Publisher: Wiley
Date: 17-07-2020
DOI: 10.1111/COBI.13520
Publisher: MDPI AG
Date: 22-05-2021
DOI: 10.3390/RS13112047
Abstract: Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing their capacity to sustain bio ersity and provide ecosystem services. Understanding the extent of ecosystem degradation is critical for estimating risks to ecosystems, yet there are few existing methods to map degradation at the ecosystem scale and none using freely available satellite data for mangrove ecosystems. In this study, we developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data. Crucially, a conceptual model of mangrove ecosystem degradation was established to identify suitable remote sensing variables that support the quantitative classification model, bridging the gap between satellite-derived variables and ecosystem degradation with explicit ecological links. We applied our degradation model to two case-studies, the mangroves of Rakhine State, Myanmar, which are severely threatened by anthropogenic disturbances, and Shark River within the Everglades National Park, USA, which is periodically disturbed by severe tropical storms. Our model suggested that 40% (597 km2) of the extent of mangroves in Rakhine showed evidence of degradation. In the Everglades, the model suggested that the extent of degraded mangrove forest increased from 5.1% to 97.4% following the Category 4 Hurricane Irma in 2017. Quantitative accuracy assessments indicated the model achieved overall accuracies of 77.6% and 79.1% for the Rakhine and the Everglades, respectively. We highlight that using an ecological conceptual model as the basis for building quantitative classification models to estimate the extent of ecosystem degradation ensures the ecological relevance of the classification models. Our developed method enables researchers to move beyond only mapping ecosystem distribution to condition and degradation as well. These results can help support ecosystem risk assessments, natural capital accounting, and restoration planning and provide quantitative estimates of ecosystem degradation for new global bio ersity targets.
Publisher: Springer Science and Business Media LLC
Date: 08-12-2020
DOI: 10.1038/S41467-020-19493-3
Abstract: Many global environmental agendas, including halting bio ersity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remain poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate a globally consistent, continuous index of forest condition as determined by the degree of anthropogenic modification. Globally, only 17.4 million km 2 of forest (40.5%) has high landscape-level integrity (mostly found in Canada, Russia, the Amazon, Central Africa, and New Guinea) and only 27% of this area is found in nationally designated protected areas. Of the forest inside protected areas, only 56% has high landscape-level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally.
Publisher: Wiley
Date: 09-2022
DOI: 10.1111/GCB.16346
Abstract: A globally relevant and standardized taxonomy and framework for consistently describing land cover change based on evidence is presented, which makes use of structured land cover taxonomies and is underpinned by the Driver-Pressure-State-Impact-Response (DPSIR) framework. The Global Change Taxonomy currently lists 246 classes based on the notation 'impact (pressure)', with this encompassing the consequence of observed change and associated reason(s), and uses scale-independent terms that factor in time. Evidence for different impacts is gathered through temporal comparison (e.g., days, decades apart) of land cover classes constructed and described from Environmental Descriptors (EDs state indicators) with pre-defined measurement units (e.g., m, %) or categories (e.g., species type). Evidence for pressures, whether abiotic, biotic or human-influenced, is similarly accumulated, but EDs often differ from those used to determine impacts. Each impact and pressure term is defined separately, allowing flexible combination into 'impact (pressure)' categories, and all are listed in an openly accessible glossary to ensure consistent use and common understanding. The taxonomy and framework are globally relevant and can reference EDs quantified on the ground, retrieved/classified remotely (from ground-based, airborne or spaceborne sensors) or predicted through modelling. By providing capacity to more consistently describe change processes-including land degradation, desertification and ecosystem restoration-the overall framework addresses a wide and erse range of local to international needs including those relevant to policy, socioeconomics and land management. Actions in response to impacts and pressures and monitoring towards targets are also supported to assist future planning, including impact mitigation actions.
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 04-2018
DOI: 10.1016/J.SCITOTENV.2017.11.034
Abstract: The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem.
Start Date: 02-2019
End Date: 02-2024
Amount: $416,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 05-2019
End Date: 05-2022
Amount: $417,068.00
Funder: Australian Research Council
View Funded ActivityStart Date: 11-2019
End Date: 11-2024
Amount: $779,000.00
Funder: Australian Research Council
View Funded Activity