ORCID Profile
0000-0001-9831-681X
Current Organisations
Université Grenoble Alpes
,
Deakin University
,
Monash University
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Publisher: Elsevier BV
Date: 09-2020
Publisher: Wiley
Date: 10-01-2018
DOI: 10.1002/FEE.1747
Publisher: Wiley
Date: 02-09-2020
DOI: 10.1111/CONL.12764
Publisher: Elsevier BV
Date: 05-2017
Publisher: Springer Science and Business Media LLC
Date: 16-08-2021
Publisher: SPIE
Date: 09-07-2018
DOI: 10.1117/12.2312683
Publisher: SPIE
Date: 24-07-2014
DOI: 10.1117/12.2057262
Publisher: Wiley
Date: 26-05-2021
DOI: 10.1111/COBI.13699
Abstract: Bio ersity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in bio ersity indicators. We developed a guide to representing uncertainty and variability in bio ersity indicators. We considered the key purposes of bio ersity indicators and commonly used methods for representing uncertainty (standard error, bootstrap res ling, and jackknife res ling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high‐profile bio ersity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in bio ersity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of bio ersity indicator trends to facilitate accurate interpretation by decision makers.
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: American Association for the Advancement of Science (AAAS)
Date: 20-07-2007
Abstract: Spatially resolving the surfaces of nearby stars promises to advance our knowledge of stellar physics. Using optical long-baseline interferometry, we constructed a near-infrared image of the rapidly rotating hot star Altair with a resolution of milliarcsecond. The image clearly reveals the strong effect of gravity darkening on the highly distorted stellar photosphere. Standard models for a uniformly rotating star cannot explain our findings, which appear to result from differential rotation, alternative gravity-darkening laws, or both.
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: SPIE
Date: 24-07-2014
DOI: 10.1117/12.2055544
Publisher: SPIE
Date: 09-07-2018
DOI: 10.1117/12.2313700
Publisher: Wiley
Date: 02-2023
DOI: 10.1111/CSP2.12891
Abstract: Threatened ecosystem conservation requires an understanding of the effectiveness of management and the challenges hindering successful protection and recovery. Bringing together researchers, land managers and policymakers to identify key threats, management needs, and knowledge gaps provides a unified account of the evidence and tools needed to improve threatened ecosystem management. We undertook a research prioritization process for Australian alpine and subalpine peatlands with experts across policy, research, and management. Through in idual interviews, structured group discussions, and voting, we generated 25 priority research questions that, if addressed, would enhance our capacity to conserve peatlands. Knowledge gaps spanned four topics: understanding peatland dynamics, impacts of threats, methods to manage these, and the effectiveness of management. Consistent monitoring standards, an open‐access knowledge platform and commitment to long‐term joint research and management were identified as vital. This collaboration enabled development of a shared agenda of research priorities to target knowledge gaps for informing policy and management of threatened alpine peatlands. Our findings substantiate the importance of stronger ongoing collaboration among researchers, land managers and policymakers across jurisdictions to support conservation.
Publisher: Public Library of Science (PLoS)
Date: 04-05-2017
Publisher: Elsevier BV
Date: 11-2021
Publisher: SPIE
Date: 04-08-2016
DOI: 10.1117/12.2232656
Publisher: Springer Science and Business Media LLC
Date: 20-06-2018
Publisher: Springer Science and Business Media LLC
Date: 04-07-2018
Publisher: Wiley
Date: 11-11-2019
DOI: 10.1111/CONL.12680
Publisher: SPIE
Date: 04-08-2016
DOI: 10.1117/12.2231067
Publisher: SPIE
Date: 14-07-2008
DOI: 10.1117/12.789754
Publisher: Wiley
Date: 27-03-2023
DOI: 10.1111/COBI.14081
Abstract: Experts can provide valuable information to fill knowledge gaps in published research on management effectiveness, particularly for threatened ecosystems, for which there is often limited evidence and the need for prompt intervention to ensure their persistence. One such ecosystem, alpine peatland, is threatened by climate change and other pressures, provides vital ecosystem services, and supports unique bio ersity. In a workshop, we gathered and synthesized into an accessible format information from experts on interventions used, threat context, and intervention effectiveness for Australian alpine peatland and used this knowledge to evaluate local relevance of the global literature for this threatened ecosystem. Experts identified 15 interventions used to conserve Australian peatlands, most of which enhanced or restored peatland condition and effectively addressed erse threats. Experts’ perspectives and global studies were strongly aligned, suggesting that research on peatland management may be broadly relevant across contexts, despite the distinct characteristics of Australian systems. Our workshop‐based expert elicitation approach provided insights into current management practices unavailable in the literature.
No related grants have been discovered for Jessica Rowland.