1
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Rowland JA, Bland LM, James S, Nicholson E. A guide to representing variability and uncertainty in biodiversity indicators. Conserv Biol 2021; 35:1669-1682. [PMID: 33486826 DOI: 10.1111/cobi.13699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 11/29/2020] [Accepted: 01/07/2021] [Indexed: 06/12/2023]
Abstract
Biodiversity 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 biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high-profile biodiversity 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 biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.
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Affiliation(s)
- Jessica A Rowland
- Centre of Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, Victoria, 3216, Australia
| | - Lucie M Bland
- Centre of Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, Victoria, 3216, Australia
- Lucie Bland Editing, Thornbury, Victoria, Australia
| | - Simon James
- School of Information Technology, Deakin University, Geelong, Victoria, Australia
| | - Emily Nicholson
- Centre of Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, Victoria, 3216, Australia
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2
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Watermeyer KE, Guillera-Arroita G, Bal P, Burgass MJ, Bland LM, Collen B, Hallam C, Kelly LT, McCarthy MA, Regan TJ, Stevenson S, Wintle BA, Nicholson E. Using decision science to evaluate global biodiversity indices. Conserv Biol 2021; 35:492-501. [PMID: 32557849 DOI: 10.1111/cobi.13574] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 06/05/2020] [Accepted: 06/12/2020] [Indexed: 06/11/2023]
Abstract
Global biodiversity indices are used to measure environmental change and progress toward conservation goals, yet few indices have been evaluated comprehensively for their capacity to detect trends of interest, such as declines in threatened species or ecosystem function. Using a structured approach based on decision science, we qualitatively evaluated 9 indices commonly used to track biodiversity at global and regional scales against 5 criteria relating to objectives, design, behavior, incorporation of uncertainty, and constraints (e.g., costs and data availability). Evaluation was based on reference literature for indices available at the time of assessment. We identified 4 key gaps in indices assessed: pathways to achieving goals (means objectives) were not always clear or relevant to desired outcomes (fundamental objectives); index testing and understanding of expected behavior was often lacking; uncertainty was seldom acknowledged or accounted for; and costs of implementation were seldom considered. These gaps may render indices inadequate in certain decision-making contexts and are problematic for indices linked with biodiversity targets and sustainability goals. Ensuring that index objectives are clear and their design is underpinned by a model of relevant processes are crucial in addressing the gaps identified by our assessment. Uptake and productive use of indices will be improved if index performance is tested rigorously and assumptions and uncertainties are clearly communicated to end users. This will increase index accuracy and value in tracking biodiversity change and supporting national and global policy decisions, such as the post-2020 global biodiversity framework of the Convention on Biological Diversity.
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Affiliation(s)
- Kate E Watermeyer
- Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, VIC, 3125, Australia
| | | | - Payal Bal
- School of BioSciences, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Michael J Burgass
- Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, U.K
- Department of Zoology, University of Oxford, Oxford, OX1 3SZ, U.K
- Biodiversify, Newark, Nottinghamshire, NG24, U.K
| | - Lucie M Bland
- Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, VIC, 3125, Australia
- School of BioSciences, University of Melbourne, Parkville, VIC, 3010, Australia
- Lucie Bland Editing, 1-3 Theobald Street, Thornbury, VIC, 3071, Australia
| | - Ben Collen
- Centre for Biodiversity and Environment Research, Department of Genetic, Evolution and Environment, University College London, London, WC1E 6BT, U.K
| | - Chris Hallam
- School of BioSciences, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Luke T Kelly
- School of Ecosystem and Forest Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Michael A McCarthy
- School of BioSciences, University of Melbourne, Parkville, VIC, 3010, Australia
- ARC Centre of Excellence for Environmental Decisions, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Tracey J Regan
- School of BioSciences, University of Melbourne, Parkville, VIC, 3010, Australia
- Arthur Rylah Institute for Environmental Research, Department of Environment, Land, Water and Planning, Heidelberg, VIC, 3084, Australia
| | - Simone Stevenson
- Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, VIC, 3125, Australia
| | - Brendan A Wintle
- Quantitative and Applied Ecology, School of Biosciences, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Emily Nicholson
- Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, VIC, 3125, Australia
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3
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Gallagher RV, Falster DS, Maitner BS, Salguero-Gómez R, Vandvik V, Pearse WD, Schneider FD, Kattge J, Poelen JH, Madin JS, Ankenbrand MJ, Penone C, Feng X, Adams VM, Alroy J, Andrew SC, Balk MA, Bland LM, Boyle BL, Bravo-Avila CH, Brennan I, Carthey AJR, Catullo R, Cavazos BR, Conde DA, Chown SL, Fadrique B, Gibb H, Halbritter AH, Hammock J, Hogan JA, Holewa H, Hope M, Iversen CM, Jochum M, Kearney M, Keller A, Mabee P, Manning P, McCormack L, Michaletz ST, Park DS, Perez TM, Pineda-Munoz S, Ray CA, Rossetto M, Sauquet H, Sparrow B, Spasojevic MJ, Telford RJ, Tobias JA, Violle C, Walls R, Weiss KCB, Westoby M, Wright IJ, Enquist BJ. Open Science principles for accelerating trait-based science across the Tree of Life. Nat Ecol Evol 2020; 4:294-303. [PMID: 32066887 DOI: 10.1038/s41559-020-1109-6] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Accepted: 01/10/2020] [Indexed: 01/22/2023]
Abstract
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.
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Affiliation(s)
- Rachael V Gallagher
- Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia.
| | - Daniel S Falster
- Evolution and Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Brian S Maitner
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA
| | - Roberto Salguero-Gómez
- Department of Zoology, Oxford University, Oxford, UK.,Centre for Biodiversity and Conservation Science, University of Queensland, Brisbane, Queensland, Australia.,Evolutionary Demography Laboratory, Max Plank Institute for Demographic Research, Rostock, Germany
| | - Vigdis Vandvik
- Department of Biological Sciences, University of Bergen, Bergen, Norway.,Bjerknes Centre for Climate Research, University of Bergen, Bergen, Norway
| | - William D Pearse
- Ecology Center and Department of Biology, Utah State University, Logan, UT, USA
| | | | - Jens Kattge
- Max Planck Institute for Biogeochemistry, Jena, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | | | - Joshua S Madin
- Hawai'i Institute of Marine Biology, University of Hawai'i at Manoa, Manoa, HI, USA
| | - Markus J Ankenbrand
- Department of Bioinformatics, Biocenter, University of Wuerzburg, Wuerzburg, Germany.,Center for Computational and Theoretical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany.,Comprehensive Heart Failure Center, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Caterina Penone
- Institute of Plant Sciences, University of Bern, Bern, Switzerland
| | - Xiao Feng
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA
| | - Vanessa M Adams
- Discipline of Geography and Spatial Sciences, University of Tasmania, Hobart, Tasmania, Australia
| | - John Alroy
- Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Samuel C Andrew
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, Australian Capital Territory, Australia
| | - Meghan A Balk
- Bio5 Institute, University of Arizona, Tucson, AZ, USA
| | - Lucie M Bland
- School of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin University, Geelong, Victoria, Australia
| | - Brad L Boyle
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA
| | - Catherine H Bravo-Avila
- Department of Biology, University of Miami, Miami, FL, USA.,Fairchild Tropical Botanic Garden, Coral Gables, FL, USA
| | - Ian Brennan
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Alexandra J R Carthey
- Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Renee Catullo
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Brittany R Cavazos
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA
| | - Dalia A Conde
- Species360 Conservation Science Alliance, Bloomington, MN, USA.,Interdisciplinary Center on Population Dynamics, University of Southern Denmark, Odense, Denmark.,Department of Biology, University of Southern Denmark, Odense, Denmark
| | - Steven L Chown
- School of Biological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Belen Fadrique
- Department of Biology, University of Miami, Miami, FL, USA
| | - Heloise Gibb
- Department of Ecology, Environment and Evolution and Centre for Future Landscapes, La Trobe University, Melbourne, Victoria, Australia
| | - Aud H Halbritter
- Department of Biological Sciences, University of Bergen, Bergen, Norway.,Bjerknes Centre for Climate Research, University of Bergen, Bergen, Norway
| | - Jennifer Hammock
- National Museum of Natural History, Smithsonian Institution, Washington, DC, USA
| | - J Aaron Hogan
- International Center for Tropical Botany, Department of Biological Sciences, Florida International University, Miami, FL, USA
| | - Hamish Holewa
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, Australian Capital Territory, Australia
| | - Michael Hope
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, Australian Capital Territory, Australia
| | - Colleen M Iversen
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Malte Jochum
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.,Institute of Plant Sciences, University of Bern, Bern, Switzerland.,Institute of Biology, Leipzig University, Leipzig, Germany
| | - Michael Kearney
- School of BioSciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alexander Keller
- Department of Bioinformatics, Biocenter, University of Wuerzburg, Wuerzburg, Germany.,Center for Computational and Theoretical Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany
| | - Paula Mabee
- Department of Biology, University of South Dakota, Vermillion, SD, USA
| | - Peter Manning
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt, Germany
| | - Luke McCormack
- Center for Tree Science, The Morton Arboretum, Lisle, IL, USA
| | - Sean T Michaletz
- Department of Botany and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Daniel S Park
- Department of Organismic and Evolutionary Biology and Harvard University Herbaria, Harvard University, Cambridge, MA, USA
| | - Timothy M Perez
- Department of Biology, University of Miami, Miami, FL, USA.,Fairchild Tropical Botanic Garden, Coral Gables, FL, USA
| | - Silvia Pineda-Munoz
- School of Biological Sciences and School of Earth & Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Courtenay A Ray
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Maurizio Rossetto
- National Herbarium of New South Wales, Royal Botanic Gardens and Domain Trust, Sydney, New South Wales, Australia.,Queensland Alliance of Agriculture and Food Innovation, University of Queensland, Brisbane, Queensland, Australia
| | - Hervé Sauquet
- Evolution and Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia.,National Herbarium of New South Wales, Royal Botanic Gardens and Domain Trust, Sydney, New South Wales, Australia.,Ecologie Systématique Evolution, Univ. Paris-Sud, CNRS, AgroParisTech, Universite Paris-Saclay, Orsay, France
| | - Benjamin Sparrow
- TERN / School of Biological Sciences, Faculty of Science, The University of Adelaide, Adelaide, South Australia, Australia
| | - Marko J Spasojevic
- Department of Evolution, Ecology, and Organismal Biology, University of California Riverside, Riverside, CA, USA
| | - Richard J Telford
- Department of Biological Sciences, University of Bergen, Bergen, Norway.,Bjerknes Centre for Climate Research, University of Bergen, Bergen, Norway
| | - Joseph A Tobias
- Department of Life Sciences, Imperial College London, London, UK
| | - Cyrille Violle
- CEFE, CNRS, Univ Montpellier, Université Paul Valéry Montpellier, Montpellier, France
| | | | | | - Mark Westoby
- Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Ian J Wright
- Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Brian J Enquist
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA.,Santa Fe Institute, Santa Fe, NM, USA
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4
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Rowland JA, Bland LM, Keith DA, Juffe‐Bignoli D, Burgman MA, Etter A, Ferrer‐Paris JR, Miller RM, Skowno AL, Nicholson E. Ecosystem indices to support global biodiversity conservation. Conserv Lett 2019. [DOI: 10.1111/conl.12680] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Affiliation(s)
- Jessica A. Rowland
- Centre of Integrative Ecology, School of Life and Environmental SciencesDeakin University Victoria Australia
| | - Lucie M. Bland
- Centre of Integrative Ecology, School of Life and Environmental SciencesDeakin University Victoria Australia
| | - David A. Keith
- Centre for Ecosystem ScienceUniversity of NSW Sydney Australia
- New South Wales Department of PlanningIndustry and Environment
- IUCN Commission on Ecosystem Management Gland Switzerland
| | - Diego Juffe‐Bignoli
- United Nations Environment Programme World Conservation Monitoring Centre (UNEP‐WCMC) Cambridge UK
| | - Mark A. Burgman
- Centre for Environmental PolicyImperial College London London UK
| | - Andres Etter
- Departmento de Ecología y Territorio, Facultad de Estudios Ambientales y RuralesPontificia Universidad Javeriana Bogotá DC Colombia
| | | | | | - Andrew L. Skowno
- South African National Biodiversity Institute (SANBI)Kirstebosch Research Centre Cape Town South Africa
- Department of Biological SciencesUniversity of Cape Town Cape Town South Africa
| | - Emily Nicholson
- Centre of Integrative Ecology, School of Life and Environmental SciencesDeakin University Victoria Australia
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5
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Bland LM, Nicholson E, Miller RM, Andrade A, Carré A, Etter A, Ferrer‐Paris JR, Herrera B, Kontula T, Lindgaard A, Pliscoff P, Skowno A, Valderrábano M, Zager I, Keith DA. Impacts of the IUCN Red List of Ecosystems on conservation policy and practice. Conserv Lett 2019. [DOI: 10.1111/conl.12666] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Lucie M. Bland
- School of Life and Environmental Sciences, Centre for Integrative Ecology Deakin University Burwood Victoria Australia
| | - Emily Nicholson
- School of Life and Environmental Sciences, Centre for Integrative Ecology Deakin University Burwood Victoria Australia
- IUCN Commission on Ecosystem Management Gland Switzerland
| | | | - Angela Andrade
- IUCN Commission on Ecosystem Management Gland Switzerland
- Conservation International Bogota Colombia
| | | | - Andres Etter
- Facultad de Estudios Ambientales y Rurales Pontificia Universidad Javeriana Bogotá Colombia
| | - José Rafael Ferrer‐Paris
- Centro de Estudios Botánicos y Agroforestales Instituto Venezolano de Investigaciones Científicas Maracaibo Venezuela
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Science University of New South Wales Kensington 2052 New South Wales Australia
- Provita Caracas Venezuela
| | - Bernal Herrera
- IUCN Commission on Ecosystem Management Gland Switzerland
- University of Costa Rica San José Costa Rica
| | | | - Arild Lindgaard
- Norwegian Biodiversity Information Centre (Artsdatabanken) Trondheim Norway
| | - Patricio Pliscoff
- Instituto de Geografía y Departamento de Ecología Pontificia Universidad Católica de Chile Santiago Chile
| | - Andrew Skowno
- South African National Biodiversity Institute Kirstenbosch Research Centre Cape Town South Africa
| | | | - Irene Zager
- IUCN Commission on Ecosystem Management Gland Switzerland
- Provita Caracas Venezuela
| | - David A. Keith
- IUCN Commission on Ecosystem Management Gland Switzerland
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Science University of New South Wales Kensington 2052 New South Wales Australia
- New South Wales Office of Environment and Heritage New South Wales Australia
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6
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Hossain MA, Kujala H, Bland LM, Burgman M, Lahoz‐Monfort JJ. Assessing the impacts of uncertainty in climate‐change vulnerability assessments. DIVERS DISTRIB 2019. [DOI: 10.1111/ddi.12936] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Md Anwar Hossain
- School of BioSciences The University of Melbourne Parkville Victoria Australia
| | - Heini Kujala
- School of BioSciences The University of Melbourne Parkville Victoria Australia
| | - Lucie M. Bland
- Centre for Integrative Ecology, School of Life and Environmental Sciences Deakin University Burwood Victoria Australia
| | - Mark Burgman
- Centre for Environmental Policy Imperial College London London UK
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7
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Doherty TS, Bland LM, Bryan BA, Neale T, Nicholson E, Ritchie EG, Driscoll DA. Expanding the Role of Targets in Conservation Policy. Trends Ecol Evol 2018; 33:809-812. [DOI: 10.1016/j.tree.2018.08.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 08/21/2018] [Accepted: 08/31/2018] [Indexed: 10/28/2022]
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8
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Hossain MA, Lahoz-Monfort JJ, Burgman MA, Böhm M, Kujala H, Bland LM. Assessing the vulnerability of freshwater crayfish to climate change. DIVERS DISTRIB 2018. [DOI: 10.1111/ddi.12831] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Affiliation(s)
- Md Anwar Hossain
- School of BioSciences; The University of Melbourne; Parkville Victoria Australia
| | | | - Mark A. Burgman
- Centre for Environmental Policy; Imperial College London; London UK
| | - Monika Böhm
- Institute of Zoology; Zoological Society of London; Regent's Park; London UK
| | - Heini Kujala
- School of BioSciences; The University of Melbourne; Parkville Victoria Australia
| | - Lucie M. Bland
- Centre for Integrative Ecology; School of Life and Environmental Sciences; Deakin University; Burwood Victoria Australia
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9
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Murray NJ, Keith DA, Bland LM, Ferrari R, Lyons MB, Lucas R, Pettorelli N, Nicholson E. The role of satellite remote sensing in structured ecosystem risk assessments. Sci Total Environ 2018; 619-620:249-257. [PMID: 29149749 DOI: 10.1016/j.scitotenv.2017.11.034] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 11/03/2017] [Accepted: 11/03/2017] [Indexed: 05/19/2023]
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.
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Affiliation(s)
- Nicholas J Murray
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, New South Wales, Australia; School of Biological Sciences, University of Queensland, St. Lucia, Queensland 4072, Australia.
| | - David A Keith
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, New South Wales, Australia; New South Wales Office of Environment and Heritage, Hurstville, New South Wales, Australia.
| | - Lucie M Bland
- Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology (Burwood Campus), 221 Burwood Highway, Burwood, VIC 3125, Australia.
| | - Renata Ferrari
- Australian Institute of Marine Science, Townsville, 4810, Australia
| | - Mitchell B Lyons
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, New South Wales, Australia.
| | - Richard Lucas
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, New South Wales, Australia.
| | - Nathalie Pettorelli
- Institute of Zoology, Zoological Society of London, Regent's Park, NW1 4RY London, UK.
| | - Emily Nicholson
- Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology (Burwood Campus), 221 Burwood Highway, Burwood, VIC 3125, Australia.
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10
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Bland LM, Regan TJ, Dinh MN, Ferrari R, Keith DA, Lester R, Mouillot D, Murray NJ, Nguyen HA, Nicholson E. Using multiple lines of evidence to assess the risk of ecosystem collapse. Proc Biol Sci 2018; 284:rspb.2017.0660. [PMID: 28931744 PMCID: PMC5627190 DOI: 10.1098/rspb.2017.0660] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Accepted: 08/10/2017] [Indexed: 11/23/2022] Open
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.
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Affiliation(s)
- Lucie M Bland
- Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, 3121, Victoria, Australia .,School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
| | - Tracey J Regan
- The Arthur Rylah Institute for Environmental Research, the Department of Environment, Land, Water and Planning, 123 Brown Street, Heidelberg, 3084, Victoria, Australia
| | - Minh Ngoc Dinh
- Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia
| | - Renata Ferrari
- Coastal and Marine Ecosystems Group, School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - David A Keith
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia.,New South Wales Office of Environment and Heritage, Hurstville, 2220, New South Wales, Australia.,Long Term Ecological Research Network, Terrestrial Ecosystem Research Network, Australian National University, Canberra, 0200, Australian Capital Territory, Australia
| | - Rebecca Lester
- Deakin University, Australia, Centre for Regional and Rural Futures, Geelong, 3220, Victoria, Australia
| | - David Mouillot
- UMR 5119-Écologie des Systèmes marins côtiers, Université Montpellier 2, Montpellier Cedex 5, France.,ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, 4881, Queensland, Australia
| | - Nicholas J Murray
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia
| | - Hoang Anh Nguyen
- Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia
| | - Emily Nicholson
- Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, 3121, Victoria, Australia
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Bland LM, Bielby J, Kearney S, Orme CDL, Watson JEM, Collen B. Toward reassessing data-deficient species. Conserv Biol 2017; 31:531-539. [PMID: 27696559 DOI: 10.1111/cobi.12850] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Revised: 08/14/2016] [Accepted: 09/29/2016] [Indexed: 06/06/2023]
Abstract
One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data-deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data-deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data-deficient assessments. To develop this, we reviewed 2879 data-deficient assessments in 6 animal groups and identified 8 main justifications for assigning data-deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data-deficient species slipping unnoticed toward extinction.
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Affiliation(s)
- Lucie M Bland
- School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Jon Bielby
- Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, U.K
| | - Stephen Kearney
- School of Geography, Planning and Environmental Management, University of Queensland, St. Lucia, QLD, 4072, Australia
| | - C David L Orme
- Division of Biology, Imperial College London, Silwood Park, Ascot, SL5 7PY, U.K
| | - James E M Watson
- School of Geography, Planning and Environmental Management, University of Queensland, St. Lucia, QLD, 4072, Australia
- Wildlife Conservation Society, Global Conservation Programs, Bronx, NY, 10460, U.S.A
| | - Ben Collen
- Centre for Biodiversity and Environment Research, University College London, Gower Street, London, WC1 E6BT, U.K
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Darrah SE, Bland LM, Bachman SP, Clubbe CP, Trias-Blasi A. Using coarse-scale species distribution data to predict extinction risk in plants. DIVERS DISTRIB 2017. [DOI: 10.1111/ddi.12532] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Affiliation(s)
- Sarah E. Darrah
- United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC); Cambridge CB3 0DL UK
| | - Lucie M. Bland
- School of BioSciences; The University of Melbourne; Parkville VIC 3010 Australia
| | - Steven P. Bachman
- Royal Botanic Gardens, Kew; Richmond Surrey TW9 3AB UK
- School of Geography; University of Nottingham; Nottingham NG7 2RD UK
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Murray NJ, Keith DA, Bland LM, Nicholson E, Regan TJ, Rodríguez JP, Bedward M. The use of range size to assess risks to biodiversity from stochastic threats. DIVERS DISTRIB 2017. [DOI: 10.1111/ddi.12533] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- Nicholas J. Murray
- Centre for Ecosystem Science School of Biological, Earth and Environmental Science University of New South Wales Sydney NSW Australia
| | - David A. Keith
- Centre for Ecosystem Science School of Biological, Earth and Environmental Science University of New South Wales Sydney NSW Australia
- New South Wales Office of Environment and Heritage Hurstville NSW Australia
| | - Lucie M. Bland
- School of Biosciences University of Melbourne Melbourne Vic. Australia
| | - Emily Nicholson
- School of Life and Environmental Sciences Centre for Integrative Ecology Deakin University Burwood Vic. Australia
| | - Tracey J. Regan
- The Department of Environment, Land, Water and Planning Arthur Rylah Institute for Environmental Research 123 Brown St Heidelberg Vic. 3084 Australia
| | - Jon Paul Rodríguez
- Centro de Ecología Instituto Venezolano de Investigaciones Científicas Apdo. 20632 Caracas 1020‐A Venezuela
- Provita Apdo. 47552 Caracas 1041‐A Venezuela
- Species Survival Commission and Commission on Ecosystem Management International Union for Conservation of Nature Rue Mauverney 28 Gland 1196 Switzerland
| | - Michael Bedward
- School of Biological Sciences University of Wollongong Wollongong NSW Australia
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Rodríguez JP, Keith DA, Rodríguez-Clark KM, Murray NJ, Nicholson E, Regan TJ, Miller RM, Barrow EG, Bland LM, Boe K, Brooks TM, Oliveira-Miranda MA, Spalding M, Wit P. A practical guide to the application of the IUCN Red List of Ecosystems criteria. Philos Trans R Soc Lond B Biol Sci 2015; 370:20140003. [PMID: 25561664 DOI: 10.1098/rstb.2014.0003] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The newly developed IUCN Red List of Ecosystems is part of a growing toolbox for assessing risks to biodiversity, 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 Biodiversity 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 biodiversity yet achieved.
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Affiliation(s)
- Jon Paul Rodríguez
- Centro de Ecología, Instituto Venezolano de Investigaciones Científicas, Apdo. 20632, Caracas 1020-A, Venezuela Provita, Apdo. 47552, Caracas 1041-A, Venezuela IUCN Commission on Ecosystem Management, Rue Mauverney 28, 1196 Gland, Switzerland IUCN Species Survival Commission, Rue Mauverney 28, 1196 Gland, Switzerland
| | - David A Keith
- IUCN Commission on Ecosystem Management, Rue Mauverney 28, 1196 Gland, Switzerland IUCN Species Survival Commission, Rue Mauverney 28, 1196 Gland, Switzerland Centre for Ecosystem Science, University of New South Wales, Sydney, New South Wales, Australia New South Wales Office of Environment and Heritage, Hurstville, New South Wales, Australia
| | - Kathryn M Rodríguez-Clark
- Centro de Ecología, Instituto Venezolano de Investigaciones Científicas, Apdo. 20632, Caracas 1020-A, Venezuela
| | - Nicholas J Murray
- Centre for Ecosystem Science, University of New South Wales, Sydney, New South Wales, Australia ARC Centre of Excellence for Environmental Decisions, School of Biological Sciences, The University of Queensland, St Lucia, Queensland 4072, Australia
| | - Emily Nicholson
- ARC Centre of Excellence for Environmental Decisions, School of Botany, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Tracey J Regan
- ARC Centre of Excellence for Environmental Decisions, School of Botany, The University of Melbourne, Parkville, Victoria 3010, Australia
| | | | | | - Lucie M Bland
- ARC Centre of Excellence for Environmental Decisions, School of Botany, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Kaia Boe
- IUCN, Rue Mauverney 28, 1196 Gland, Switzerland
| | | | | | - Mark Spalding
- The Nature Conservancy and Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Piet Wit
- IUCN Commission on Ecosystem Management, Rue Mauverney 28, 1196 Gland, Switzerland
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Affiliation(s)
- Lucie M. Bland
- School of BioSciences; The University of Melbourne; Parkville Vic. 3010 Australia
- Division of Biology; Imperial College London; Silwood Park Ascot SL5 7PY UK
- Institute of Zoology; Zoological Society of London; Regent's Park London NW1 4RY UK
| | - C. David L. Orme
- Division of Biology; Imperial College London; Silwood Park Ascot SL5 7PY UK
| | - Jon Bielby
- Institute of Zoology; Zoological Society of London; Regent's Park London NW1 4RY UK
| | - Ben Collen
- Centre for Biodiversity and Environment Research; University College London; Gower Street London WC1 E6BT UK
| | - Emily Nicholson
- School of BioSciences; The University of Melbourne; Parkville Vic. 3010 Australia
- School of Life and Environmental Sciences; Deakin University; Burwood Vic. 3125 Australia
| | - Michael A. McCarthy
- School of BioSciences; The University of Melbourne; Parkville Vic. 3010 Australia
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Bland LM, Collen B, Orme CDL, Bielby J. Predicting the conservation status of data-deficient species. Conserv Biol 2015; 29:250-9. [PMID: 25124400 DOI: 10.1111/cobi.12372] [Citation(s) in RCA: 124] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2013] [Accepted: 05/12/2014] [Indexed: 05/19/2023]
Abstract
There is little appreciation of the level of extinction risk faced by one-sixth of the over 65,000 species assessed by the International Union for Conservation of Nature. Determining the status of these data-deficient (DD) species is essential to developing an accurate picture of global biodiversity and identifying potentially threatened DD species. To address this knowledge gap, we used predictive models incorporating species' life history, geography, and threat information to predict the conservation status of DD terrestrial mammals. We constructed the models with 7 machine learning (ML) tools trained on species of known status. The resultant models showed very high species classification accuracy (up to 92%) and ability to correctly identify centers of threatened species richness. Applying the best model to DD species, we predicted 313 of 493 DD species (64%) to be at risk of extinction, which increases the estimated proportion of threatened terrestrial mammals from 22% to 27%. Regions predicted to contain large numbers of threatened DD species are already conservation priorities, but species in these areas show considerably higher levels of risk than previously recognized. We conclude that unless directly targeted for monitoring, species classified as DD are likely to go extinct without notice. Taking into account information on DD species may therefore help alleviate data gaps in biodiversity indicators and conserve poorly known biodiversity.
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Affiliation(s)
- Lucie M Bland
- Institute of Zoology, Zoological Society of London, Regent's Park, London NW1 4RY, United Kingdom; Division of Biology, Imperial College London, Silwood Park, Ascot, SL5 7PY, United Kingdom.
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Affiliation(s)
- Lucie M. Bland
- Institute of Zoology; Zoological Society of London; Regent's Park London NW1 4RY UK
- Division of Biology; Imperial College London; Silwood Park Ascot SL5 7PY UK
| | - Ben Collen
- Institute of Zoology; Zoological Society of London; Regent's Park London NW1 4RY UK
| | - C. David L. Orme
- Division of Biology; Imperial College London; Silwood Park Ascot SL5 7PY UK
| | - Jon Bielby
- Institute of Zoology; Zoological Society of London; Regent's Park London NW1 4RY UK
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