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Curti JN, Barton M, Flores RG, Lechner M, Lipman A, Montgomery GA, Park AY, Rochel K, Tingley MW. Using unstructured crowd-sourced data to evaluate urban tolerance of terrestrial native animal species within a California Mega-City. PLoS One 2024; 19:e0295476. [PMID: 38809860 PMCID: PMC11135677 DOI: 10.1371/journal.pone.0295476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/18/2024] [Indexed: 05/31/2024] Open
Abstract
In response to biodiversity loss and biotic community homogenization in urbanized landscapes, there are increasing efforts to conserve and increase biodiversity within urban areas. Accordingly, around the world, previously extirpated species are (re)colonizing and otherwise infiltrating urban landscapes, while other species are disappearing from these landscapes. Tracking the occurrence of traditionally urban intolerant species and loss of traditionally urban tolerant species should be a management goal of urban areas, but we generally lack tools to study this phenomenon. To address this gap, we first used species' occurrences from iNaturalist, a large collaborative dataset of species observations, to calculate an urban association index (UAI) for 967 native animal species that occur in the city of Los Angeles. On average, the occurrence of native species was negatively associated with our composite measure of urban intensity, with the exception of snails and slugs, which instead occur more frequently in areas of increased urban intensity. Next, we assessed 8,348 0.25 x 0.25 mile grids across the City of Los Angeles to determine the average grid-level UAI scores (i.e., a summary of the UAIs present in a grid cell, which we term Community Urban Tolerance Index or CUTI). We found that areas of higher urban intensity host more urban tolerant species, but also that taxonomic groups differ in their aggregate tolerance of urban areas, and that spatial patterns of tolerance vary between groups. The framework established here has been designed to be iteratively reevaluated by city managers of Los Angeles in order to track the progress of initiatives to preserve and encourage urban biodiversity, but can be rescaled to sample different regions within the city or different cities altogether to provide a valuable tool for city managers globally.
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Affiliation(s)
- Joseph N. Curti
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, United States of America
| | - Michelle Barton
- LA Sanitation and Environment, Los Angeles City, CA, United States of America
| | - Rhay G. Flores
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, United States of America
| | - Maren Lechner
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, United States of America
| | - Alison Lipman
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, United States of America
| | - Graham A. Montgomery
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, United States of America
| | - Albert Y. Park
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, United States of America
| | - Kirstin Rochel
- LA Sanitation and Environment, Los Angeles City, CA, United States of America
| | - Morgan W. Tingley
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, United States of America
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2
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Hartig F, Abrego N, Bush A, Chase JM, Guillera-Arroita G, Leibold MA, Ovaskainen O, Pellissier L, Pichler M, Poggiato G, Pollock L, Si-Moussi S, Thuiller W, Viana DS, Warton DI, Zurell D, Yu DW. Novel community data in ecology-properties and prospects. Trends Ecol Evol 2024; 39:280-293. [PMID: 37949795 DOI: 10.1016/j.tree.2023.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 11/12/2023]
Abstract
New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.
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Affiliation(s)
- Florian Hartig
- Theoretical Ecology, University of Regensburg, Regensburg, Germany.
| | - Nerea Abrego
- Department of Biological and Environmental Science, University of Jyväskylä, P.O. Box 35 (Survontie 9C), FI-40014 Jyväskylä, Finland
| | - Alex Bush
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Jonathan M Chase
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | | | | | - Otso Ovaskainen
- Department of Biological and Environmental Science, University of Jyväskylä, P.O. Box 35 (Survontie 9C), FI-40014 Jyväskylä, Finland; Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, P.O. Box 65, Helsinki 00014, Finland
| | - Loïc Pellissier
- Ecosystems and Landscape Evolution, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, 8092 Zurich, Switzerland; Unit of Land Change Science, Swiss Federal Research Institute for Forest, Snow and Landscape Research (WSL), 8903 Birmensdorf, Switzerland
| | | | - Giovanni Poggiato
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, F38000, Grenoble, France
| | - Laura Pollock
- Department of Biology, McGill University, Montreal, Quebec, Canada
| | - Sara Si-Moussi
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, F38000, Grenoble, France
| | - Wilfried Thuiller
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, F38000, Grenoble, France
| | | | | | | | - Douglas W Yu
- Kunming Institute of Zoology; Yunnan, China; University of East Anglia, Norfolk, UK
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3
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Tekwa E, Gonzalez A, Zurell D, O'Connor M. Detecting and attributing the causes of biodiversity change: needs, gaps and solutions. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220181. [PMID: 37246389 DOI: 10.1098/rstb.2022.0181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 04/11/2023] [Indexed: 05/30/2023] Open
Abstract
This issue addresses the multifaceted problems of understanding biodiversity change to meet emerging international development and conservation goals, national economic accounting and diverse community needs. Recent international agreements highlight the need to establish monitoring and assessment programmes at national and regional levels. We identify an opportunity for the research community to develop the methods for robust detection and attribution of biodiversity change that will contribute to national assessments and guide conservation action. The 16 contributions of this issue address six major aspects of biodiversity assessment: connecting policy to science, establishing observation, improving statistical estimation, detecting change, attributing causes and projecting the future. These studies are led by experts in Indigenous studies, economics, ecology, conservation, statistics, and computer science, with representations from Asia, Africa, South America, North America and Europe. The results place biodiversity science in the context of policy needs and provide an updated roadmap for how to observe biodiversity change in a way that supports conservation action via robust detection and attribution science. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.
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Affiliation(s)
- Eden Tekwa
- Department of Zoology and Biodiversity Research Centre, The University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z4
- Department of Biology, McGill University, Montreal, Quebec, Canada H3A 1B1
- Hakai Institute, Heriot Bay, British Columbia, Canada V0P 1H0
| | - Andrew Gonzalez
- Department of Biology, McGill University, Montreal, Quebec, Canada H3A 1B1
| | - Damaris Zurell
- Institute for Biochemistry and Biology, University of Potsdam, 14469 Potsdam, Germany
| | - Mary O'Connor
- Department of Zoology and Biodiversity Research Centre, The University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z4
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4
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Obligation to Enhance OBIS Data for Sea- and Shorebirds of the Americas. DIVERSITY 2022. [DOI: 10.3390/d14121099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The distributions of many sea- and shorebird species span large geographic areas, making them ideal candidates as biomonitors of ecosystem perturbations and long-term environmental trends. The basic question examined in this study was: Does a major open-access data archive contain sufficient temporal- and spatial-scale data to support more detailed inquiry into multi-decadal-scale responses in geographic distributions of specific taxa? The global-scale open-access data platform, Ocean Biodiversity Information System (OBIS), was searched to compile data on bird distributions of the Americas, including the Caribbean Sea. More than 680,000 occurrence records of 210 species, collected between 1965 and 2018, were located and evaluated by marine ecoregion. The Puget Trough/Georgia Basin marine ecoregion, along the United States/Canadian border, and the Virginian marine ecoregion on the US east coast, dominated occurrences, each with more than 100,000 records, while the Gulf of Maine/Bay of Fundy had the most years of records (42). Most records from South America (~29,000) came from the Channels and Fjords of Southern Chile, collected across 16 different years. More than 90% of the recorded data were collected since 1983, and more than 95% of the records were from North American marine ecoregions. We urge additional observations to be shared via OBIS to allow comprehensive large-scale and detailed meta-analyses of spatial and temporal trends in marine and shore-bird communities and their biodiversity.
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Streit RP, Bellwood DR. To harness traits for ecology, let’s abandon ‘functionality’. Trends Ecol Evol 2022; 38:402-411. [PMID: 36522192 DOI: 10.1016/j.tree.2022.11.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 11/16/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022]
Abstract
Traits are measurable features of organisms. Functional traits aspire to more. They quantify an organism's ecology and, ultimately, predict ecosystem functions based on local communities. Such predictions are useful, but only if 'functional' really means 'ecologically relevant'. Unfortunately, many 'functional' traits seem to be characterized primarily by availability and implied importance - not by their ecological information content. Better traits are needed, but a prevailing trend is to 'functionalize' existing traits. The key may be to invert the process, that is, to identify functions of interest first and then identify traits as quantifiable proxies. We propose two distinct, yet complementary, perspectives on traits and provide a 'taxonomy of traits', a conceptual compass to navigate the diverse applications of traits in ecology.
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Koch W, Elven H, Finstad AG. Clavis: An open and versatile identification key format. PLoS One 2022; 17:e0277752. [PMID: 36454899 PMCID: PMC9714862 DOI: 10.1371/journal.pone.0277752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 11/02/2022] [Indexed: 12/03/2022] Open
Abstract
The skills and knowledge needed to recognize and classify taxa are becoming increasingly scarce in the scientific community. At the same time, it is clear that these skills are strongly needed in biodiversity monitoring for management and conservation, especially when carried out by citizen scientists. Formalizing the required knowledge in the form of digital identification keys is one way of making such knowledge more available for professional and amateur observers of biodiversity. In this paper we describe Clavis, an open and versatile data format for capturing the knowledge required for taxon identification through digital keys, allowing for a level of detail beyond that of any current key format. We present the format independently from any particular implementation, as our aim is for Clavis to serve as a basis for interoperable tools and interfaces serving different needs and actors.
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Affiliation(s)
- Wouter Koch
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
- Norwegian Biodiversity Information Centre, Trondheim, Norway
- * E-mail:
| | - Hallvard Elven
- Natural History Museum, University of Oslo, Oslo, Norway
| | - Anders G. Finstad
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
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7
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Lindenmayer DB, Woinarski J, Legge S, Maron M, Garnett ST, Lavery T, Dielenberg J, Wintle BA. Eight things you should never do in a monitoring program: an Australian perspective. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:701. [PMID: 35995962 PMCID: PMC9395441 DOI: 10.1007/s10661-022-10348-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 08/11/2022] [Indexed: 06/15/2023]
Abstract
Monitoring is critical to gauge the effect of environmental management interventions as well as to measure the effects of human disturbances such as climate change. Recognition of the critical need for monitoring means that, at irregular intervals, recommendations are made for new government-instigated programs or to revamp existing ones. Using insights from past well-intentioned (but sadly also often failed) attempts to establish and maintain government-instigated monitoring programs in Australia, we outline eight things that should never be done in environmental monitoring programs (if they aim to be useful). These are the following: (1) Never commence a new environmental management initiative without also committing to a monitoring program. (2) Never start a monitoring program without clear questions. (3) Never implement a monitoring program without first doing a proper experimental design. (4) Never ignore the importance of matching the purpose and objectives of a monitoring program to the design of that program. (5) Never change the way you monitor something without ensuring new methods can be calibrated with the old ones. (6) Never try to monitor everything. (7) Never collect data without planning to curate and report on it. (8) If possible, avoid starting a monitoring program without the necessary resources secured. To balance our "nevers", we provide a checklist of actions that will increase the chances a monitoring program will actually measure the effectiveness of environmental management. Scientists and resource management practitioners need to be part of a stronger narrative for, and key participants in, well-designed, implemented, and maintained government-led monitoring programs. We argue that monitoring programs should be mandated in threatened species conservation programs and all new environmental management initiatives.
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Affiliation(s)
- David B Lindenmayer
- Fenner School of Environment & Society, The Australian National University, Australian Capital Territory, Canberra, Australia.
| | - John Woinarski
- Research Institute of Environment and Livelihoods, Charles Darwin University, Northern Territory, Australia
| | - Sarah Legge
- Fenner School of Environment & Society, The Australian National University, Australian Capital Territory, Canberra, Australia
| | - Martine Maron
- School of Earth and Environmental Sciences, The University of Queensland, St Lucia, Australia
| | - Stephen T Garnett
- Research Institute of Environment and Livelihoods, Charles Darwin University, Northern Territory, Australia
| | - Tyrone Lavery
- Fenner School of Environment & Society, The Australian National University, Australian Capital Territory, Canberra, Australia
| | - Jaana Dielenberg
- Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, QLD, Australia
| | - Brendan A Wintle
- School of Ecosystem and Forest Science, University of Melbourne, Parkville, VIC, Australia
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8
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Alagador D, Cerdeira JO. Operations research applicability in spatial conservation planning. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 315:115172. [PMID: 35525048 DOI: 10.1016/j.jenvman.2022.115172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/12/2022] [Accepted: 04/23/2022] [Indexed: 06/14/2023]
Abstract
A large fraction of the current environmental crisis derives from the large rates of human-driven biodiversity loss. Biodiversity conservation questions human practices towards biodiversity and, therefore, largely conflicts with ordinary societal aspirations. Decisions on the location of protected areas, one of the most convincing conservation tools, reflect such a competitive endeavor. Operations Research (OR) brings a set of analytical models and tools capable of resolving the conflicting interests between ecology and economy. Recent technological advances have boosted the size and variety of data available to planners, thus challenging conventional approaches bounded on optimized solutions. New models and methods are needed to use such a massive amount of data in integrative schemes addressing a large variety of concerns. This study provides an overview on the past, present and future challenges that characterize spatial conservation models supported by OR. We discuss the progress of OR models and methods in spatial conservation planning and how those models may be optimized through sophisticated algorithms and computational tools. Moreover, we anticipate possible panoramas of modern spatial conservation studies supported by OR and we explore possible avenues for the design of optimized interdisciplinary collaborative platforms in the era of Big Data, through consortia where distinct players with different motivations and services meet. By enlarging the spatial, temporal, taxonomic and societal horizons of biodiversity conservation, planners navigate around multiple socioecological/environmental equilibria and are able to decide on cost-effective strategies to improve biodiversity persistence under complex environments.
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Affiliation(s)
- Diogo Alagador
- Biodiversity Chair, Institute for Advanced Studies and Research, Universidade de Évora, Rua Joaquim Henrique da Fonseca, Casa Cordovil, 2°, 7000-890, Évora, Portugal; MED - Mediterranean Institute for Agriculture, Environment and Development, CHANGE - Global Change and Sustainability Institute, Universidade de Évora, Évora, Portugal.
| | - Jorge Orestes Cerdeira
- Department of Mathematics, Faculdade de Ciências e Tecnologia da Universidade NOVA de Lisboa, Quinta da Torre, 282 -516, Costa da Caparica, Portugal; Centre for Mathematics and Applications, Faculdade de Ciências e Tecnologia da Universidade NOVA de Lisboa, Quinta da Torre, 282 -516, Costa da Caparica, Portugal.
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9
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Lannuzel G, Pouget L, Bruy D, Hequet V, Meyer S, Munzinger J, Gâteblé G. Mining rare Earth elements: Identifying the plant species most threatened by ore extraction in an insular hotspot. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.952439] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Conservation efforts in global biodiversity hotspots often face a common predicament: an urgent need for conservation action hampered by a significant lack of knowledge about that biodiversity. In recent decades, the computerisation of primary biodiversity data worldwide has provided the scientific community with raw material to increase our understanding of the shared natural heritage. These datasets, however, suffer from a lot of geographical and taxonomic inaccuracies. Automated tools developed to enhance their reliability have shown that detailed expert examination remains the best way to achieve robust and exhaustive datasets. In New Caledonia, one of the most important biodiversity hotspots worldwide, the plant diversity inventory is still underway, and most taxa awaiting formal description are narrow endemics, hence by definition hard to discern in the datasets. In the meantime, anthropogenic pressures, such as nickel-ore mining, are threatening the unique ultramafic ecosystems at an increasing rate. The conservation challenge is therefore a race against time, as the rarest species must be identified and protected before they vanish. In this study, based on all available datasets and resources, we applied a workflow capable of highlighting the lesser known taxa. The main challenges addressed were to aggregate all data available worldwide, and tackle the geographical and taxonomic biases, avoiding the data loss resulting from automated filtering. Every doubtful specimen went through a careful taxonomic analysis by a local and international taxonomist panel. Geolocation of the whole dataset was achieved through dataset cross-checking, local botanists’ field knowledge, and historical material examination. Field studies were also conducted to clarify the most unresolved taxa. With the help of this method and by analysing over 85,000 data, we were able to double the number of known narrow endemic taxa, elucidate 68 putative new species, and update our knowledge of the rarest species’ distributions so as to promote conservation measures.
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10
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Bowler DE, Bhandari N, Repke L, Beuthner C, Callaghan CT, Eichenberg D, Henle K, Klenke R, Richter A, Jansen F, Bruelheide H, Bonn A. Decision-making of citizen scientists when recording species observations. Sci Rep 2022; 12:11069. [PMID: 35773384 PMCID: PMC9245884 DOI: 10.1038/s41598-022-15218-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 06/21/2022] [Indexed: 11/16/2022] Open
Abstract
Citizen scientists play an increasingly important role in biodiversity monitoring. Most of the data, however, are unstructured—collected by diverse methods that are not documented with the data. Insufficient understanding of the data collection processes presents a major barrier to the use of citizen science data in biodiversity research. We developed a questionnaire to ask citizen scientists about their decision-making before, during and after collecting and reporting species observations, using Germany as a case study. We quantified the greatest sources of variability among respondents and assessed whether motivations and experience related to any aspect of data collection. Our questionnaire was answered by almost 900 people, with varying taxonomic foci and expertise. Respondents were most often motivated by improving species knowledge and supporting conservation, but there were no linkages between motivations and data collection methods. By contrast, variables related to experience and knowledge, such as membership of a natural history society, were linked with a greater propensity to conduct planned searches, during which typically all species were reported. Our findings have implications for how citizen science data are analysed in statistical models; highlight the importance of natural history societies and provide pointers to where citizen science projects might be further developed.
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Affiliation(s)
- Diana E Bowler
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany. .,Institute of Biodiversity, Friedrich Schiller University Jena, Dornburger Str. 159, 07743, Jena, Germany. .,Department of Ecosystem Services, Helmholtz-Center for Environmental Research - UFZ, Permoserstraße 15, 04318, Leipzig, Germany.
| | - Netra Bhandari
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany
| | - Lydia Repke
- Department of Survey Design and Methodology, GESIS - Leibniz Institute for the Social Sciences, P.O. Box 12 21 55, 68072, Mannheim, Germany
| | - Christoph Beuthner
- Department of Survey Design and Methodology, GESIS - Leibniz Institute for the Social Sciences, P.O. Box 12 21 55, 68072, Mannheim, Germany
| | - Corey T Callaghan
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany.,Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108, Halle, Germany
| | - David Eichenberg
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany.,Department of Ecosystem Services, Helmholtz-Center for Environmental Research - UFZ, Permoserstraße 15, 04318, Leipzig, Germany
| | - Klaus Henle
- Department of Conservation Biology & Social-Ecological Systems, Helmholtz-Center for Environmental Research - UFZ, Permoserstraße 15, 04318, Leipzig, Germany
| | - Reinhard Klenke
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany.,Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108, Halle, Germany
| | - Anett Richter
- Thünen Institute of Biodiversity, Bundesallee 65, 38116, Braunschweig, Germany
| | - Florian Jansen
- Faculty of Agricultural and Environmental Sciences, University of Rostock, Justus-von-Liebig-Weg 6, 18059, Rostock, Germany
| | - Helge Bruelheide
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany.,Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108, Halle, Germany
| | - Aletta Bonn
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany.,Institute of Biodiversity, Friedrich Schiller University Jena, Dornburger Str. 159, 07743, Jena, Germany.,Department of Ecosystem Services, Helmholtz-Center for Environmental Research - UFZ, Permoserstraße 15, 04318, Leipzig, Germany
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11
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Leitão ATTS, Alves MDDO, dos Santos JCP, Bezerra B. Instagram as a data source for sea turtle surveys in shipwrecks in Brazil. Anim Conserv 2022. [DOI: 10.1111/acv.12802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- A. T. T. S. Leitão
- Programa de Pós‐graduação em Biologia Animal, Laboratório de Ecologia Comportamento e Conservação, Departamento de Zoologia, Centro de Biociências Universidade Federal de Pernambuco Recife Brazil
| | - M. D. de O Alves
- Departamento de Ciências Biológicas Faculdade Frassinetti do Recife – FAFIRE Recife Brazil
| | - J. C. P. dos Santos
- Universidade Federal Rural de Pernambuco UFRPE / Unidade Acadêmica de Serra Talhada – UAST Serra Talhada Brazil
| | - B. Bezerra
- Programa de Pós‐graduação em Biologia Animal, Laboratório de Ecologia Comportamento e Conservação, Departamento de Zoologia, Centro de Biociências Universidade Federal de Pernambuco Recife Brazil
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12
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Maximizing citizen scientists' contribution to automated species recognition. Sci Rep 2022; 12:7648. [PMID: 35538130 PMCID: PMC9090737 DOI: 10.1038/s41598-022-11257-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 04/11/2022] [Indexed: 11/24/2022] Open
Abstract
Technological advances and data availability have enabled artificial intelligence-driven tools that can increasingly successfully assist in identifying species from images. Especially within citizen science, an emerging source of information filling the knowledge gaps needed to solve the biodiversity crisis, such tools can allow participants to recognize and report more poorly known species. This can be an important tool in addressing the substantial taxonomic bias in biodiversity data, where broadly recognized, charismatic species are highly over-represented. Meanwhile, the recognition models are trained using the same biased data, so it is important to consider what additional images are needed to improve recognition models. In this study, we investigated how the amount of training data influenced the performance of species recognition models for various taxa. We utilized a large citizen science dataset collected in Norway, where images are added independently from identification. We demonstrate that while adding images of currently under-represented taxa will generally improve recognition models more, there are important deviations from this general pattern. Thus, a more focused prioritization of data collection beyond the basic paradigm that “more is better” is likely to significantly improve species recognition models and advance the representativeness of biodiversity data.
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13
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Johnston A, Matechou E, Dennis E. Outstanding challenges and future directions for biodiversity monitoring using citizen science data. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13834] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Alison Johnston
- Centre for Research into Ecological and Environmental Modelling, Department of Maths and Statistics University of St Andrews St Andrews UK
- Cornell Lab of Ornithology, 159 Sapsucker Woods Road Ithaca NY USA
| | - Eleni Matechou
- School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury Kent UK
| | - Emily Dennis
- School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury Kent UK
- Butterfly Conservation, Manor Yard, East Lulworth, Wareham Dorset UK
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14
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Moussy C, Burfield IJ, Stephenson PJ, Newton AFE, Butchart SHM, Sutherland WJ, Gregory RD, McRae L, Bubb P, Roesler I, Ursino C, Wu Y, Retief EF, Udin JS, Urazaliyev R, Sánchez-Clavijo LM, Lartey E, Donald PF. A quantitative global review of species population monitoring. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2022; 36:e13721. [PMID: 33595149 DOI: 10.1111/cobi.13721] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 01/28/2021] [Accepted: 02/10/2021] [Indexed: 06/12/2023]
Abstract
Species monitoring, defined here as the repeated, systematic collection of data to detect long-term changes in the populations of wild species, is a vital component of conservation practice and policy. We created a database of nearly 1200 schemes, ranging in start date from 1800 to 2018, to review spatial, temporal, taxonomic, and methodological patterns in global species monitoring. We identified monitoring schemes through standardized web searches, an online survey of stakeholders, in-depth national searches in a sample of countries, and a review of global biodiversity databases. We estimated the total global number of monitoring schemes operating at 3300-15,000. Since 2000, there has been a sharp increase in the number of new schemes being initiated in lower- and middle-income countries and in megadiverse countries, but a decrease in high-income countries. The total number of monitoring schemes in a country and its per capita gross domestic product were strongly, positively correlated. Schemes that were active in 2018 had been running for an average of 21 years in high-income countries, compared with 13 years in middle-income countries and 10 years in low-income countries. In high-income countries, over one-half of monitoring schemes received government funding, but this was less than one-quarter in low-income countries. Data collection was undertaken partly or wholly by volunteers in 37% of schemes, and such schemes covered significantly more sites and species than those undertaken by professionals alone. Birds were by far the most widely monitored taxonomic group, accounting for around half of all schemes, but this bias declined over time. Monitoring in most taxonomic groups remains sparse and uncoordinated, and most of the data generated are elusive and unlikely to feed into wider biodiversity conservation processes. These shortcomings could be addressed by, for example, creating an open global meta-database of biodiversity monitoring schemes and enhancing capacity for species monitoring in countries with high biodiversity. Article impact statement: Species population monitoring for conservation purposes remains strongly biased toward a few vertebrate taxa in wealthier countries.
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Affiliation(s)
| | | | - P J Stephenson
- IUCN SSC Species Monitoring Specialist Group, Gingins, Switzerland
- Science & Economic Knowledge Unit, IUCN, Gland, Switzerland
| | | | - Stuart H M Butchart
- BirdLife International, Cambridge, UK
- Department of Zoology, Conservation Science Group, University of Cambridge, Cambridge, UK
| | - William J Sutherland
- Department of Zoology, Conservation Science Group, University of Cambridge, Cambridge, UK
| | - Richard D Gregory
- RSPB Centre for Conservation Science, Bedfordshire, UK
- Centre for Biodiversity & Environment Research, Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Louise McRae
- Institute of Zoology, Zoological Society of London, London, UK
| | - Philip Bubb
- UN Environment World Conservation Monitoring Centre, Cambridge, UK
| | - Ignacio Roesler
- Scientific Department, Aves Argentinas, Buenos Aires, Argentina
| | - Cynthia Ursino
- Scientific Department, Aves Argentinas, Buenos Aires, Argentina
| | - Yanqing Wu
- Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing, P.R. China
| | - Ernst F Retief
- Science and Innovation Programme, BirdLife South Africa, Johannesburg, South Africa
| | | | - Ruslan Urazaliyev
- Association for the Conservation of Biodiversity of Kazakhstan, Nur-Sultan, Kazakhstan
| | - Lina M Sánchez-Clavijo
- Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, Bogotá, Colombia
| | | | - Paul F Donald
- BirdLife International, Cambridge, UK
- Department of Zoology, Conservation Science Group, University of Cambridge, Cambridge, UK
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15
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Picek L, Šulc M, Matas J, Heilmann-Clausen J, Jeppesen TS, Lind E. Automatic Fungi Recognition: Deep Learning Meets Mycology. SENSORS 2022; 22:s22020633. [PMID: 35062595 PMCID: PMC8779018 DOI: 10.3390/s22020633] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/03/2022] [Accepted: 01/04/2022] [Indexed: 02/04/2023]
Abstract
The article presents an AI-based fungi species recognition system for a citizen-science community. The system's real-time identification too - FungiVision - with a mobile application front-end, led to increased public interest in fungi, quadrupling the number of citizens collecting data. FungiVision, deployed with a human-in-the-loop, reaches nearly 93% accuracy. Using the collected data, we developed a novel fine-grained classification dataset - Danish Fungi 2020 (DF20) - with several unique characteristics: species-level labels, a small number of errors, and rich observation metadata. The dataset enables the testing of the ability to improve classification using metadata, e.g., time, location, habitat and substrate, facilitates classifier calibration testing and finally allows the study of the impact of the device settings on the classification performance. The continual flow of labelled data supports improvements of the online recognition system. Finally, we present a novel method for the fungi recognition service, based on a Vision Transformer architecture. Trained on DF20 and exploiting available metadata, it achieves a recognition error that is 46.75% lower than the current system. By providing a stream of labeled data in one direction, and an accuracy increase in the other, the collaboration creates a virtuous cycle helping both communities.
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Affiliation(s)
- Lukáš Picek
- Department of Cybernetics, Faculty of Applied Sciences, University of West Bohemia, 30100 Pilsen, Czech Republic
- Correspondence: or
| | - Milan Šulc
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 16636 Prague, Czech Republic; (M.Š.); (J.M.)
| | - Jiří Matas
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 16636 Prague, Czech Republic; (M.Š.); (J.M.)
| | - Jacob Heilmann-Clausen
- Center for Macroecology, Evolution and Climate, Biological Institute, University of Copenhagen, 1165 Copenhagen, Denmark; (J.H.-C.); (E.L.)
| | | | - Emil Lind
- Center for Macroecology, Evolution and Climate, Biological Institute, University of Copenhagen, 1165 Copenhagen, Denmark; (J.H.-C.); (E.L.)
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16
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Knape J, Coulson SJ, van der Wal R, Arlt D. Temporal trends in opportunistic citizen science reports across multiple taxa. AMBIO 2022; 51:183-198. [PMID: 33782853 PMCID: PMC8651922 DOI: 10.1007/s13280-021-01550-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/18/2021] [Accepted: 03/02/2021] [Indexed: 06/12/2023]
Abstract
Opportunistic reporting of species observations to online platforms provide one of the most extensive sources of information about the distribution and status of organisms in the wild. The lack of a clear sampling design, and changes in reporting over time, leads to challenges when analysing these data for temporal change in organisms. To better understand temporal changes in reporting, we use records submitted to an online platform in Sweden (Artportalen), currently containing 80 million records. Focussing on five taxonomic groups, fungi, plants, beetles, butterflies and birds, we decompose change in reporting into long-term and seasonal trends, and effects of weekdays, holidays and weather variables. The large surge in number of records since the launch of the, initially taxa-specific, portals is accompanied by non-trivial long-term and seasonal changes that differ between the taxonomic groups and are likely due to changes in, and differences between, the user communities and observer behaviour.
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Affiliation(s)
- Jonas Knape
- Department of Ecology, Swedish University of Agricultural Sciences, Inst för Ekologi, Box 7044, 75007 Uppsala, Sweden
| | - Stephen James Coulson
- Swedish Species Information Centre, Swedish University of Agricultural Sciences, Almas Allé 8E, Box 7007, 750 07 Uppsala, Sweden
- Department of Arctic Biology, University Centre in Svalbard, UNIS, Box 156, 9171 Longyearbyen, Norway
| | - René van der Wal
- Department of Ecology, Swedish University of Agricultural Sciences, Inst för Ekologi, Box 7044, 75007 Uppsala, Sweden
| | - Debora Arlt
- Department of Ecology, Swedish University of Agricultural Sciences, Inst för Ekologi, Box 7044, 75007 Uppsala, Sweden
- Swedish Species Information Centre, Swedish University of Agricultural Sciences, Almas Allé 8E, Box 7007, 750 07 Uppsala, Sweden
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17
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Townsend PA, Clare JDJ, Liu N, Stenglein JL, Anhalt‐Depies C, Van Deelen TR, Gilbert NA, Singh A, Martin KJ, Zuckerberg B. Snapshot Wisconsin: networking community scientists and remote sensing to improve ecological monitoring and management. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2021; 31:e02436. [PMID: 34374154 PMCID: PMC9286556 DOI: 10.1002/eap.2436] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 03/25/2021] [Accepted: 04/21/2021] [Indexed: 06/13/2023]
Abstract
Biological data collection is entering a new era. Community science, satellite remote sensing (SRS), and local forms of remote sensing (e.g., camera traps and acoustic recordings) have enabled biological data to be collected at unprecedented spatial and temporal scales and resolution. There is growing interest in developing observation networks to collect and synthesize data to improve broad-scale ecological monitoring, but no examples of such networks have emerged to inform decision-making by agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin, which links synoptic environmental data derived from SRS to biodiversity observations collected continuously from a trail camera network to support management decision-making. We use several examples to illustrate that Snapshot Wisconsin improves the spatial, temporal, and biological resolution and extent of information available to support management, filling gaps associated with traditional monitoring and enabling consideration of new management strategies. JONs like Snapshot Wisconsin further strengthen monitoring inference by contributing novel lines of evidence useful for corroboration or integration. SRS provides environmental context that facilitates inference, prediction, and forecasting, and ultimately helps managers formulate, test, and refine conceptual models for the monitored systems. Although these approaches pose challenges, Snapshot Wisconsin demonstrates that expansive observation networks can be tractably managed by agencies to support decision making, providing a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.
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Affiliation(s)
- Philip A. Townsend
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - John D. J. Clare
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Nanfeng Liu
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | | | - Christine Anhalt‐Depies
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
- Wisconsin Department of Natural ResourcesMadisonWisconsin53707USA
| | - Timothy R. Van Deelen
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Neil A. Gilbert
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Aditya Singh
- Department of Agricultural and Biological EngineeringUniversity of FloridaGainesvilleFlorida32603USA
| | - Karl J. Martin
- Division of ExtensionUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
| | - Benjamin Zuckerberg
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsin53706USA
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18
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Pierce JR, Drill S, Halder MD, Tan MMJ, Tiwari A, López Guijosa PA. Scaling Biodiversity Conservation Efforts: An Examination of the Relationship Between Global Biodiversity Targets and Local Plans. FRONTIERS IN CONSERVATION SCIENCE 2021. [DOI: 10.3389/fcosc.2021.752387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Cities have a critical role to play in meeting global-scale biodiversity targets. Urban socio-ecological systems connect human and ecological well-being. The outsized impact of cities reaches well-beyond their geographic borders through cultural, ecological, and economic interactions. Although cities account for just 2% of the earth's surface, they host over half of the human population and are responsible for 75% of consumption. The Parties to the Convention on Biological Diversity (CBD) and others have acknowledged the important role cities can play in achieving global targets. In response, at least 110 cities have produced plans focused on biodiversity, but we do not know the extent to which these city plans align with global targets or what role they play in achieving these targets. Here, we explore the relationship between global biodiversity conservation targets and local biodiversity plans to identify how elements at the two scales align or diverge. We compared the CBD Strategic Plan 2011–2020 (Aichi Targets) with 44 local biodiversity plans (often called LBSAPs) from cities around the world. We analyzed more than 2,800 actions from the local plans to measure the relationship with these global targets. Our results show how local approaches to biodiversity conservation can inform post-2020 global frameworks to improve coordination between global and local scale processes. We identify actions particular to the local scale that are critical to conserve global biodiversity and suggest a framework for improved coordination between actors at different scales that address their respective roles and spheres of influence.
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19
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Mandeville CP, Koch W, Nilsen EB, Finstad AG. Open Data Practices among Users of Primary Biodiversity Data. Bioscience 2021; 71:1128-1147. [PMID: 34733117 PMCID: PMC8560312 DOI: 10.1093/biosci/biab072] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Presence-only biodiversity data are increasingly relied on in biodiversity, ecology, and conservation research, driven by growing digital infrastructures that support open data sharing and reuse. Recent reviews of open biodiversity data have clearly documented the value of data sharing, but the extent to which the biodiversity research community has adopted open data practices remains unclear. We address this question by reviewing applications of presence-only primary biodiversity data, drawn from a variety of sources beyond open databases, in the indexed literature. We characterize how frequently researchers access open data relative to data from other sources, how often they share newly generated or collated data, and trends in metadata documentation and data citation. Our results indicate that biodiversity research commonly relies on presence-only data that are not openly available and neglects to make such data available. Improved data sharing and documentation will increase the value, reusability, and reproducibility of biodiversity research.
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Affiliation(s)
- Caitlin P Mandeville
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
| | - Wouter Koch
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
| | - Erlend B Nilsen
- Faculty of Biosciences and Aquaculture, Nord University, Steinkjer, Norway
| | - Anders G Finstad
- Department of Natural History, Norwegian University of Science and Technology, Trondheim, Norway
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20
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Big Data in Biodiversity Science: A Framework for Engagement. TECHNOLOGIES 2021. [DOI: 10.3390/technologies9030060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Despite best efforts, the loss of biodiversity has continued at a pace that constitutes a major threat to the efficient functioning of ecosystems. Curbing the loss of biodiversity and assessing its local and global trends requires a vast amount of datasets from a variety of sources. Although the means for generating, aggregating and analyzing big datasets to inform policies are now within the reach of the scientific community, the data-driven nature of a complex multidisciplinary field such as biodiversity science necessitates an overarching framework for engagement. In this review, we propose such a schematic based on the life cycle of data to interrogate the science. The framework considers data generation and collection, storage and curation, access and analysis and, finally, communication as distinct yet interdependent themes for engaging biodiversity science for the purpose of making evidenced-based decisions. We summarize historical developments in each theme, including the challenges and prospects, and offer some recommendations based on best practices.
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21
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Global and national trends, gaps, and opportunities in documenting and monitoring species distributions. PLoS Biol 2021; 19:e3001336. [PMID: 34383738 PMCID: PMC8360587 DOI: 10.1371/journal.pbio.3001336] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 06/22/2021] [Indexed: 11/25/2022] Open
Abstract
Conserving and managing biodiversity in the face of ongoing global change requires sufficient evidence to assess status and trends of species distributions. Here, we propose novel indicators of biodiversity data coverage and sampling effectiveness and analyze national trajectories in closing spatiotemporal knowledge gaps for terrestrial vertebrates (1950 to 2019). Despite a rapid rise in data coverage, particularly in the last 2 decades, strong geographic and taxonomic biases persist. For some taxa and regions, a tremendous growth in records failed to directly translate into newfound knowledge due to a sharp decline in sampling effectiveness. However, we found that a nation’s coverage was stronger for species for which it holds greater stewardship. As countries under the post-2020 Global Biodiversity Framework renew their commitments to an improved, rigorous biodiversity knowledge base, our findings highlight opportunities for international collaboration to close critical information gaps. Conserving and managing biodiversity in the face of ongoing global change requires sufficient evidence to assess status and trends of species distributions. This study analyzes national trajectories in closing spatiotemporal knowledge gaps for terrestrial vertebrates (1950-2019) based on novel indicators of data coverage and sampling effectiveness.
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22
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Stenhouse A, Perry T, Grützner F, Lewis M, Koh LP. EchidnaCSI – Improving monitoring of a cryptic species at continental scale using Citizen Science. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2021.e01626] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
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23
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Caution over the use of ecological big data for conservation. Nature 2021; 595:E17-E19. [DOI: 10.1038/s41586-021-03463-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 03/16/2021] [Indexed: 11/09/2022]
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24
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Sun CC, Hurst JE, Fuller AK. Citizen Science Data Collection for Integrated Wildlife Population Analyses. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.682124] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Citizen science, or community science, has emerged as a cost-efficient method to collect data for wildlife monitoring. To inform research and conservation, citizen science sampling designs should collect data that match the robust statistical analyses needed to quantify species and population patterns. Further increasing the contributions of citizen science, integrating citizen science data with other datasets and datatypes can improve population estimates and expand the spatiotemporal extent of inference. We demonstrate these points with a citizen science program called iSeeMammals developed in New York state in 2017 to supplement costly systematic spatial capture-recapture sampling by collecting opportunistic data from one-off observations, hikes, and camera traps. iSeeMammals has initially focused on the growing population of American black bear (Ursus americanus), with integrated analysis of iSeeMammals camera trap data with systematic data for a region with a growing bear population. The triumvirate of increased spatial and temporal coverage by at least twofold compared to systematic sampling, an 83% reduction in annual sampling costs, and improved density estimates when integrated with systematic data highlight the benefits of collecting presence-absence data in citizen science programs for estimating population patterns. Additional opportunities will come from applying presence-only data, which are oftentimes more prevalent than presence-absence data, to integrated models. Patterns in data submission and filtering also emphasize the importance of iteratively evaluating patterns in engagement, usability, and accessibility, especially focusing on younger adult and teenage demographics, to improve data quality and quantity. We explore how the development and use of integrated models may be paired with citizen science project design in order to facilitate repeated use of datasets in standalone and integrated analyses for supporting wildlife monitoring and informing conservation.
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25
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García MB, Silva JL, Tejero P, Pardo I. Detecting early‐warning signals of concern in plant populations with a Citizen Science network. Are threatened and other priority species for conservation performing worse? J Appl Ecol 2021. [DOI: 10.1111/1365-2664.13890] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | | | - Pablo Tejero
- Pyrenean Institute of Ecology (CSIC) Zaragoza Spain
| | - Iker Pardo
- Pyrenean Institute of Ecology (CSIC) Zaragoza Spain
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26
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Rosa C, Baccaro F, Cronemberger C, Hipólito J, Barros CF, Rodrigues DDEJ, Neckel-Oliveira S, Overbeck GE, Drechsler-Santos ER, Anjos MRD, Ferreguetti ÁC, Akama A, Martins MB, Tomas WM, Santos SA, Ferreira VL, Cunha CNDA, Penha J, Pinho JBDE, Salis SM, Doria CRDAC, Pillar VD, Podgaiski LR, Menin M, Bígio NC, Aragón S, Manzatto AG, Vélez-Martin E, Silva ACBLE, Izzo TJ, Mortati AF, Giacomin LL, Almeida TE, André T, Silveira MAPDEA, Silveira ALPDA, Messias MR, Marques MCM, Padial AA, Marques R, Bitar YOC, Silveira M, Morato EF, Pagotto RDEC, Strussmann C, Machado RB, Aguiar LMDES, Fernandes GW, Oki Y, Novais S, Ferreira GB, Barbosa FR, Ochoa AC, Mangione AM, Gatica A, Carrizo MC, Retta LM, Jofré LE, Castillo LL, Neme AM, Rueda C, Toledo JJDE, Grelle CEV, Vale MM, Vieira MV, Cerqueira R, Higashikawa EM, Mendonça FPDE, Guerreiro QLDEM, Banhos A, Hero JM, Koblitz R, Collevatti RG, Silveira LF, Vasconcelos HL, Vieira CR, Colli GR, Cechin SZ, Santos TGD, Fontana CS, Jarenkow JA, Malabarba LR, Rueda MP, Araujo PA, Palomo L, Iturre MC, Bergallo HG, Magnusson WE. The Program for Biodiversity Research in Brazil: The role of regional networks for biodiversity knowledge, dissemination, and conservation. AN ACAD BRAS CIENC 2021; 93:e20201604. [PMID: 33852672 DOI: 10.1590/0001-3765202120201604] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/11/2021] [Indexed: 11/22/2022] Open
Abstract
The Program for Biodiversity Research (PPBio) is an innovative program designed to integrate all biodiversity research stakeholders. Operating since 2004, it has installed long-term ecological research sites throughout Brazil and its logic has been applied in some other southern-hemisphere countries. The program supports all aspects of research necessary to understand biodiversity and the processes that affect it. There are presently 161 sampling sites (see some of them at Supplementary Appendix), most of which use a standardized methodology that allows comparisons across biomes and through time. To date, there are about 1200 publications associated with PPBio that cover topics ranging from natural history to genetics and species distributions. Most of the field data and metadata are available through PPBio web sites or DataONE. Metadata is available for researchers that intend to explore the different faces of Brazilian biodiversity spatio-temporal variation, as well as for managers intending to improve conservation strategies. The Program also fostered, directly and indirectly, local technical capacity building, and supported the training of hundreds of undergraduate and graduate students. The main challenge is maintaining the long-term funding necessary to understand biodiversity patterns and processes under pressure from global environmental changes.
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Affiliation(s)
- Clarissa Rosa
- Instituto Nacional de Pesquisas da Amazônia, Coordenação de Biodiversidade, Av. André Araújo 2936, Petrópolis, 69067-375 Manaus, AM, Brazil
| | - Fabricio Baccaro
- Universidade Federal do Amazonas, Departamento de Biologia, Instituto de Ciências Biológicas, Av. General Rodrigo Otávio Jordão Ramos, 6200, Coroado, 69080-900 Manaus, AM, Brazil
| | - Cecilia Cronemberger
- Instituto Chico Mendes de Conservação da Biodiversidade, Parque Nacional da Serra dos Órgãos, Av. Rotariana, s/n, Soberbo, 25960-602 Teresópolis, RJ, Brazil.,Universidade do Estado do Rio de Janeiro, Programa de Pós-Graduação em Meio Ambiente, Rua São Francisco Xavier, 524, Maracanã, 20550-900 Rio de Janeiro, RJ, Brazil
| | - Juliana Hipólito
- Instituto Nacional de Pesquisas da Amazônia, Coordenação de Biodiversidade, Av. André Araújo 2936, Petrópolis, 69067-375 Manaus, AM, Brazil
| | - Claudia Franca Barros
- Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Diretoria de Pesquisas, Rua Pacheco Leão, 915, Jardim Botânico, 22460-030 Rio de Janeiro, RJ, Brazil
| | - Domingos DE Jesus Rodrigues
- Universidade Federal de Mato Grosso, Instituto de Ciências Naturais, Humanas e Sociais, Av. Alexandre Ferronato, 1200, Setor Industrial, 78557-267 Sinop, MT, Brazil
| | - Selvino Neckel-Oliveira
- Universidade Federal de Santa Catarina, Departamento de Ecologia e Zoologia, Centro de Ciências Biológicas, Rua Roberto Sampaio Gonzaga, s/n, Trindade, 88040-970 Florianópolis, SC, Brazil
| | - Gerhard E Overbeck
- Universidade Federal do Rio Grande do Sul, Departamento de Botânica, Instituto de Biociências, Av. Bento Gonçalves, 9500, Agronomia, 91501-970 Porto Alegre, RS, Brazil
| | - Elisandro Ricardo Drechsler-Santos
- Universidade Federal de Santa Catarina, Departamento de Botânica, Centro de Ciências Biológicas, Rua Roberto Sampaio Gonzaga, s/n, Trindade, 88040-970 Florianópolis, SC, Brazil
| | - Marcelo Rodrigues Dos Anjos
- Universidade Federal do Amazonas, Laboratório de Ictiologia e Ordenamento Pesqueiro do Vale do Rio Madeira - LIOP, Rua Vinte e Nove de Agosto, 786, Centro, 69800-000 Humaitá, AM, Brazil
| | - Átilla C Ferreguetti
- Universidade do Estado do Rio de Janeiro, Departamento Ecologia, Rua São Francisco Xavier, 524, PHLC 220, Maracanã, 20550-013 Rio de Janeiro, RJ, Brazil
| | - Alberto Akama
- Museu Paraense Emílio Goeldi, Coordenação de Zoologia, Av. Perimetral, 1901, Terra Firme, 66077-830 Belém, PA, Brazil
| | - Marlúcia Bonifácio Martins
- Museu Paraense Emílio Goeldi, Coordenação de Zoologia, Av. Perimetral, 1901, Terra Firme, 66077-830 Belém, PA, Brazil
| | | | | | - Vanda Lúcia Ferreira
- Universidade Federal de Mato Grosso do Sul, Laboratório de Pesquisa em Herpetologia, Instituto de Biociências, Av. Costa e Silva, s/n, Universitário, Caixa Postal 549, 79070-900 Campo Grande, MS, Brazil
| | - Catia Nunes DA Cunha
- Universidade Federal do Mato Grosso, Instituto Nacional de Ciência e Tecnologia em Áreas Úmidas, (INAU-UFMT), Prédio INPP, Rua Dois, 497, Boa Esperança, 78068-360 Cuiabá, MT, Brazil
| | - Jerry Penha
- Universidade Federal de Mato Grosso, Centro de Biodiversidade, Instituto de Biociências, Av. Fernando Correa da Costa, 2367, Boa Esperança, 78060-900 Cuiabá, MT, Brazil
| | - João Batista DE Pinho
- Universidade Federal de Mato Grosso, Centro de Biodiversidade, Departamento de Botânica e Ecologia/Instituto de Biociências, Av. Fernando Correa da Costa, 2367, Boa Esperança, 78060-900 Cuiabá, MT, Brazil
| | - Suzana Maria Salis
- Embrapa Pantanal, Rua 21 de Setembro 1880, Aeroporto, 79320-900 Corumbá, MS, Brazil
| | - Carolina Rodrigues DA Costa Doria
- Universidade Federal de Rondônia, Laboratório de Ictiologia e Pesca, Departamento de Biologia, Rodovia BR 364, km 9,5 s/n, São Sebastião, 76801-972 Porto Velho, RO, Brazil
| | - Valério D Pillar
- Universidade Federal do Rio Grande do Sul, Departamento de Ecologia, Instituto de Biociências, Av. Bento Gonçalves, 9500, Agronomia, 91501-970 Porto Alegre, RS, Brazil
| | - Luciana R Podgaiski
- Universidade Federal do Rio Grande do Sul, Departamento de Ecologia, Instituto de Biociências, Av. Bento Gonçalves, 9500, Agronomia, 91501-970 Porto Alegre, RS, Brazil
| | - Marcelo Menin
- Universidade Federal do Amazonas, Departamento de Biologia, Instituto de Ciências Biológicas, Av. General Rodrigo Otávio Jordão Ramos, 6200, Coroado, 69080-900 Manaus, AM, Brazil
| | - Narcísio Costa Bígio
- Universidade Federal de Rondônia, Departamento de Biologia, Rodovia BR 364, km 9,5 s/n, São Sebastião, 76801-972 Porto Velho, RO, Brazil
| | - Susan Aragón
- Universidade Federal do Oeste do Pará, Programa de Pós-Graduação em Recursos Naturais da Amazônia, Rua Vera Paz, s/n, Salé, 68040-255 Santarém, PA, Brazil
| | - Angelo Gilberto Manzatto
- Universidade Federal de Rondônia, Departamento de Biologia, Rodovia BR 364, km 9,5 s/n, São Sebastião, 76801-972 Porto Velho, RO, Brazil
| | - Eduardo Vélez-Martin
- Universidade Federal do Rio Grande do Sul, Departamento de Ecologia, Instituto de Biociências, Av. Bento Gonçalves, 9500, Agronomia, 91501-970 Porto Alegre, RS, Brazil
| | - Ana Carolina Borges Lins E Silva
- Universidade Federal Rural de Pernambuco, Departamento de Biologia, Rua Dom Manoel de Medeiros, s/n, Dois irmãos, 52171-900 Recife, PE, Brazil
| | - Thiago Junqueira Izzo
- Universidade Federal do Mato Grosso/UFMT, Campus Cuiabá, Centro de Biodiversidade, Instituto de Biociências, Av. Fernando Correa da Costa, 2367, Boa Esperança, 78060-900 Cuiabá, MT, Brazil
| | - Amanda Frederico Mortati
- Universidade Federal do Oeste do Pará, Programa de Pós-Graduação em Biodiversidade, Rua Vera Paz, s/n, Salé, 68040-255 Santarém, PA, Brazil
| | - Leandro Lacerda Giacomin
- Universidade Federal do Oeste do Pará, Instituto de Ciências e Tecnologia das Águas & Herbário HSTM, Rua Vera Paz, s/n, Salé, 68040-255 Santarém, PA, Brazil
| | - Thaís Elias Almeida
- Universidade Federal do Oeste do Pará, Programa de Pós-Graduação em Biodiversidade, Rua Vera Paz, s/n, Salé, 68040-255 Santarém, PA, Brazil
| | - Thiago André
- Universidade Federal do Oeste do Pará, Programa de Pós-Graduação em Biodiversidade, Rua Vera Paz, s/n, Salé, 68040-255 Santarém, PA, Brazil
| | | | | | - Mariluce Rezende Messias
- Universidade Federal de Rondônia, Departamento de Biologia, Rodovia BR 364, km 9,5 s/n, São Sebastião, 76801-972 Porto Velho, RO, Brazil
| | - Marcia C M Marques
- Universidade Federal do Paraná, Departamento de Botânica, SCB, Av. Francisco H. dos Santos, 100, Jardim das Américas, 81531-980 Curitiba, PR, Brazil
| | - Andre Andrian Padial
- Universidade Federal do Paraná, Departamento de Botânica, SCB, Av. Francisco H. dos Santos, 100, Jardim das Américas, 81531-980 Curitiba, PR, Brazil
| | - Renato Marques
- Universidade Federal do Paraná, Departamento de Solos e Engenharia Agrícola, Laboratório de Biogeoquímica, Rua dos Funcionários, 1540, Cabral, 80035-050 Curitiba, PR, Brazil
| | - Youszef O C Bitar
- Universidade Federal do Pará, Laboratório de Ecologia de Comunidades, Campus Universitário do Marajó-Soure, Décima terceira rua, s/n, Centro, 68870-000 Soure, PA, Brazil
| | - Marcos Silveira
- Universidade Federal do Acre, Centro de Ciências Biológicas e da Natureza, Rodovia BR 364, Km 4, s/n, Distrito Industrial, 69915-559 Rio Branco, AC, Brazil
| | - Elder Ferreira Morato
- Universidade Federal do Acre, Centro de Ciências Biológicas e da Natureza, Rodovia BR 364, Km 4, s/n, Distrito Industrial, 69915-559 Rio Branco, AC, Brazil
| | - Rubiani DE Cássia Pagotto
- Universidade Federal de Rondônia, Departamento de Biologia, Rodovia BR 364, km 9,5 s/n, São Sebastião, 76801-972 Porto Velho, RO, Brazil
| | - Christine Strussmann
- Universidade Federal de Mato Grosso, Departamento de Ciências Básicas e Produção Animal, Av. Fernando Correa da Costa, 2367, Boa Esperança, 78060-900 Cuiabá, MT, Brazil.,Universidade Federal de Mato Grosso, Faculdade de Medicina Veterinária, Av. Fernando Correia da Costa, 2367, Boa Esperança, 78060-900 Cuiabá, MT, Brazil
| | - Ricardo Bomfim Machado
- Universidade de Brasília, Departamento de Zoologia, Campus Universitário Darcy Ribeiro, S/N, Asa Norte, 70910-900 Brasília, DF, Brazil
| | - Ludmilla Moura DE Souza Aguiar
- Universidade de Brasília, Departamento de Zoologia, Campus Universitário Darcy Ribeiro, S/N, Asa Norte, 70910-900 Brasília, DF, Brazil
| | - Geraldo Wilson Fernandes
- Universidade Federal de Minas Gerais, Departamento de Genética, Ecologia & Evolução, Instituto de Ciências Biológicas, Av. Antônio Carlos, 6627, Pampulha, Caixa Postal 486, 31270-901 Belo Horizonte, MG, Brazil
| | - Yumi Oki
- Universidade Federal de Minas Gerais, Departamento de Genética, Ecologia & Evolução, Instituto de Ciências Biológicas, Av. Antônio Carlos, 6627, Pampulha, Caixa Postal 486, 31270-901 Belo Horizonte, MG, Brazil
| | - Samuel Novais
- Universidade Federal de Minas Gerais, Departamento de Genética, Ecologia & Evolução, Instituto de Ciências Biológicas, Av. Antônio Carlos, 6627, Pampulha, Caixa Postal 486, 31270-901 Belo Horizonte, MG, Brazil
| | - Guilherme Braga Ferreira
- University College London, Centre for Biodiversity and Environment Research, Gower Street WC1E 6BT, London, UK
| | - Flávia Rodrigues Barbosa
- Universidade Federal de Mato Grosso, Instituto de Ciências Naturais, Humanas e Sociais, Av. Alexandre Ferronato, 1200, Setor Industrial, 78557-267 Sinop, MT, Brazil
| | - Ana C Ochoa
- Universidad Nacional de San Luis, Departamento de Biología, Facultad de Química Bioquímica y Farmacia, Instituto Multidisciplinario de Investigaciones Biológicas (IMIBIO), Conicet San Luis. Av. Ejército de Los Andes 950, 5700, San Luis, Argentina
| | - Antonio M Mangione
- Universidad Nacional de San Luis, Departamento de Biología, Facultad de Química Bioquímica y Farmacia, Instituto Multidisciplinario de Investigaciones Biológicas (IMIBIO), Conicet San Luis. Av. Ejército de Los Andes 950, 5700, San Luis, Argentina
| | - Ailin Gatica
- Universidad Nacional de San Luis, Departamento de Biología, Facultad de Química Bioquímica y Farmacia, Instituto Multidisciplinario de Investigaciones Biológicas (IMIBIO), Conicet San Luis. Av. Ejército de Los Andes 950, 5700, San Luis, Argentina
| | - María Celina Carrizo
- Universidad Nacional de Mar del Plata, Laboratorio de Ecología Fisiológica y del Comportamiento, Instituto de Investigaciones Marinas y Costeras (IIMyC), Dean Funes 3250, 7600, Mar del Plata, Buenos Aires, Argentina
| | - Lucía Martinez Retta
- Universidad Nacional de San Luis, Departamento de Biología, Facultad de Química Bioquímica y Farmacia, Instituto Multidisciplinario de Investigaciones Biológicas (IMIBIO), Conicet San Luis. Av. Ejército de Los Andes 950, 5700, San Luis, Argentina
| | - Laura E Jofré
- Universidad Nacional de San Luis, Departamento de Biología, Facultad de Química Bioquímica y Farmacia, Instituto Multidisciplinario de Investigaciones Biológicas (IMIBIO), Conicet San Luis. Av. Ejército de Los Andes 950, 5700, San Luis, Argentina
| | - Luciana L Castillo
- Universidad Nacional de San Luis, Departamento de Biología, Facultad de Química Bioquímica y Farmacia, Instituto Multidisciplinario de Investigaciones Biológicas (IMIBIO), Conicet San Luis. Av. Ejército de Los Andes 950, 5700, San Luis, Argentina
| | - Andrea M Neme
- Universidad Nacional de Santiago del Estero, Facultad de Ciencias Forestales, Av. Belgrano Sur 1912, Santiago del Estero, 4200, Santiago del Estero, Argentina
| | - Carla Rueda
- Universidad Nacional de Santiago del Estero, Facultad de Ciencias Forestales, Av. Belgrano Sur 1912, Santiago del Estero, 4200, Santiago del Estero, Argentina
| | - José Julio DE Toledo
- Universidade Federal do Amapá, Laboratório de Ecologia, DMAD, Rodovia Juscelino Kubitschek, Km 02, s/n, Universidade, 68903-419 Macapá, AP, Brazil
| | - Carlos Eduardo Viveiros Grelle
- Universidade Federal do Rio de Janeiro, Departamento de Ecologia, Instituto de Biologia, Av. Carlos Chagas Filho, 373, Cidade Universitária, Caixa Postal 68020, 21941-902 Rio de Janeiro, RJ, Brazil
| | - Mariana M Vale
- Universidade Federal do Rio de Janeiro, Departamento de Ecologia, Instituto de Biologia, Av. Carlos Chagas Filho, 373, Cidade Universitária, Caixa Postal 68020, 21941-902 Rio de Janeiro, RJ, Brazil
| | - Marcus Vinicius Vieira
- Universidade Federal do Rio de Janeiro, Departamento de Ecologia, Instituto de Biologia, Av. Carlos Chagas Filho, 373, Cidade Universitária, Caixa Postal 68020, 21941-902 Rio de Janeiro, RJ, Brazil
| | - Rui Cerqueira
- Universidade Federal do Rio de Janeiro, Departamento de Ecologia, Instituto de Biologia, Av. Carlos Chagas Filho, 373, Cidade Universitária, Caixa Postal 68020, 21941-902 Rio de Janeiro, RJ, Brazil
| | - Emílio Manabu Higashikawa
- Instituto Nacional de Pesquisas da Amazônia, Coordenação de Biodiversidade, Av. André Araújo 2936, Petrópolis, 69067-375 Manaus, AM, Brazil
| | - Fernando Pereira DE Mendonça
- Instituto de Educação, Ciência e Tecnologia do Amazonas, Campus Presidente Figueiredo, Av. Onça-Pintada, s/n, Centro, 69735-000 Presidente Figueiredo, AM, Brazil
| | - Quêzia Leandro DE Moura Guerreiro
- Universidade Federal do Oeste do Pará, Instituto de Ciências e Tecnologia das Águas, Rua Vera Paz, s/n, Salé, 68040-255 Santarém, PA, Brazil
| | - Aureo Banhos
- Universidade Federal do Espírito Santo, Departamento de Biologia, Centro de Ciências Exatas, Naturais e da Saúde, Alto Universitário, s/n, Guararema, Salé, 29500-000 Alegre, ES, Brazil
| | - Jean-Marc Hero
- University of the Sunshine Coast, School of Science, Technology and Engineering, Maroochydore, QLD 4558, Australia
| | - Rodrigo Koblitz
- Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis, Diretoria de Licenciamento Ambiental, Edifício Sede do Ibama/Bloco B - L4, Asa Norte, 70818-900 Brasília, DF, Brazil
| | - Rosane Garcia Collevatti
- Universidade Federal de Goiás, Laboratório de Genética & Biodiversidade, Instituto de Ciências Biológicas, Campus II Samambaia, s/n, Setor Central, 74001-970 Goiânia, GO, Brazil
| | - Luís Fábio Silveira
- Universidade de São Paulo, Museu de Zoologia, Seção de Aves, Av. Nazaré, 481, Centro, 04263-000 Ipiranga, SP, Brazil
| | - Heraldo L Vasconcelos
- Universidade Federal de Uberlândia, Instituto de Biologia, Av. Amazonas, 20, Umuarama, 38405-302 Uberlândia, MG, Brazil
| | | | - Guarino Rinaldi Colli
- Universidade de Brasília, Departamento de Zoologia, Campus Universitário Darcy Ribeiro, S/N, Asa Norte, 70910-900 Brasília, DF, Brazil
| | - Sonia Zanini Cechin
- Universidade Federal de Santa Maria, Departamento de Ecologia e Evolução, Av. Roraima, 1000, Camobi, 97105-900 Santa Maria, RS, Brazil
| | - Tiago Gomes Dos Santos
- Universidade Federal do Pampa, Av. Antônio Trilha, 1847, Centro, 97300-162 São Gabriel, RS, Brazil
| | - Carla S Fontana
- Pontifícia Universidade Católica do Rio Grande do Sul, Programa de Pós-Graduação em Ecologia e Evolução da Biodiversidade, Laboratório de Ornitologia, Museu de Ciência e Tecnologia, Av. Ipiranga, 6681, Partenon, 90619-900 Porto Alegre, RS, Brazil
| | - João A Jarenkow
- Universidade Federal do Rio Grande do Sul, Departamento de Botânica, Instituto de Biociências, Av. Bento Gonçalves, 9500, Agronomia, 91501-970 Porto Alegre, RS, Brazil
| | - Luiz R Malabarba
- Universidade Federal do Rio Grande do Sul, Departamento de Zoologia, Instituto de Biociências, Av. Bento Gonçalves, 9500, Agronomia, 91501-970 Porto Alegre, RS, Brazil
| | - Marta P Rueda
- Universidad Nacional de Santiago del Estero, Facultad de Ciencias Forestales, Av. Belgrano Sur 1912, Santiago del Estero, 4200, Santiago del Estero, Argentina
| | - Publio A Araujo
- Universidad Nacional de Santiago del Estero, Facultad de Ciencias Forestales, Av. Belgrano Sur 1912, Santiago del Estero, 4200, Santiago del Estero, Argentina
| | - Lucas Palomo
- Unión de Pequeños Productores del Salado Norte (UPPSAN), Santos Lugares, Ruta Provincial n° 2, s/n, 4203, Alberdi, Santiago del Estero, Argentina
| | - Marta C Iturre
- Universidad Nacional de Santiago del Estero, Facultad de Ciencias Forestales, Av. Belgrano Sur 1912, Santiago del Estero, 4200, Santiago del Estero, Argentina
| | - Helena Godoy Bergallo
- Universidade do Estado do Rio de Janeiro, Departamento Ecologia, Rua São Francisco Xavier, 524, PHLC 220, Maracanã, 20550-013 Rio de Janeiro, RJ, Brazil
| | - William E Magnusson
- Instituto Nacional de Pesquisas da Amazônia, Coordenação de Biodiversidade, Av. André Araújo 2936, Petrópolis, 69067-375 Manaus, AM, Brazil
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27
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Impact of Environmental, Social Values and the Consideration of Future Consequences for the Development of a Sustainable Entrepreneurial Intention. SUSTAINABILITY 2021. [DOI: 10.3390/su13052648] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Sustainable entrepreneurship focuses on finding ways to monetize future products, nature conservation, life support, and communities. Therefore, the intention has been identified as one of the key drivers to perceive business opportunities and ultimately leverage them, which increases interest in investigating it, especially from a sustainability perspective. The purpose of this study was to investigate the intention of sustainable entrepreneurship through a modified version of the theory of planned behavior based on survey data of 520 university students studying in Punjab, Pakistan and using structural equation modeling for quantitative analysis. The study sought to incorporate three additional constructs (environmental values, social values, and consideration of future consequences) to explain the relationship between the antecedents of sustainable entrepreneurial intention. This study shows that sustainable entrepreneurship, social norms, attitudes, and perceived behavioral control praise students’ sustainable intentions. Environmental values, intrinsic and extrinsic rewards, and consideration of future consequences (CFC-F and CFC-I) indirectly influence sustainable entrepreneurial intentions. The study also highlights the contradictory roles of CFC-I in reversing the pursuit of sustainable entrepreneurship. Indeed, the finding proposed that educational and other practitioners can improve attitudes and behaviors by promoting sustainable entrepreneurship through value creation and forward-looking activation strategies.
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28
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Weisshaupt N, Lehikoinen A, Mäkinen T, Koistinen J. Challenges and benefits of using unstructured citizen science data to estimate seasonal timing of bird migration across large scales. PLoS One 2021; 16:e0246572. [PMID: 33539480 PMCID: PMC7861542 DOI: 10.1371/journal.pone.0246572] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 01/21/2021] [Indexed: 11/20/2022] Open
Abstract
Millions of bird observations have been entered on online portals in the past 20 years either as checklists or arbitrary individual entries. While several hundred publications have been written on a variety of topics based on bird checklists worldwide, unstructured non-checklist observations have received little attention and praise by academia. In the present study we tested the suitability of non-checklist data to estimate key figures of large-scale migration phenology in four zones covering the whole of Finland. For that purpose, we analysed 10 years of ornithological non-checklist data including over 400 million. individuals of 115 bird species. We discuss bird- and human-induced effects to be considered in handling non-checklist data in this context and describe applied methodologies to address these effects. We calculated 5%, 50% and 95% percentile dates of spring and autumn migration period for all species in all four zones. For validation purposes we compared the temporal distributions of 43 bird species with migration phenology from standardized long-term ringing data in autumn of which 24 species (56%) showed similar medians. In a model approach, non-checklist data successfully revealed latitudinal migration progression in spring and autumn. Overall, non-checklist data proved to be well suited to determine descriptors of migration phenology in Northern Europe which are challenging to attain by any other currently available means. The effort-to-yield ratio of data processing was commensurate to the outcomes. The unprecedented spatiotemporal coverage makes non-checklist data a valuable complement to current migration databases from bird observatories. The basic concept of the present methodology is applicable to data from other bird portals, if combined with local field ornithological knowledge and literature. Species-specific descriptors of migration phenology can be potentially used in climate change studies and to support echo interpretation in radar ornithology.
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Affiliation(s)
| | - Aleksi Lehikoinen
- Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland
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29
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Carr H, Abas M, Boutahar L, Caretti ON, Chan WY, Chapman ASA, de Mendonça SN, Engleman A, Ferrario F, Simmons KR, Verdura J, Zivian A. The Aichi Biodiversity Targets: achievements for marine conservation and priorities beyond 2020. PeerJ 2020; 8:e9743. [PMID: 33391861 PMCID: PMC7759131 DOI: 10.7717/peerj.9743] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Accepted: 07/27/2020] [Indexed: 11/20/2022] Open
Abstract
In 2010 the Conference of the Parties (COP) for the Convention on Biological Diversity revised and updated a Strategic Plan for Biodiversity 2011–2020, which included the Aichi Biodiversity Targets. Here a group of early career researchers mentored by senior scientists, convened as part of the 4th World Conference on Marine Biodiversity, reflects on the accomplishments and shortfalls under four of the Aichi Targets considered highly relevant to marine conservation: target 6 (sustainable fisheries), 11 (protection measures), 15 (ecosystem restoration and resilience) and 19 (knowledge, science and technology). We conclude that although progress has been made towards the targets, these have not been fully achieved for the marine environment by the 2020 deadline. The progress made, however, lays the foundations for further work beyond 2020 to work towards the 2050 Vision for Biodiversity. We identify key priorities that must be addressed to better enable marine biodiversity conservation efforts moving forward.
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Affiliation(s)
- Hannah Carr
- The Joint Nature Conservation Committee, Peterborough, Cambridgeshire, UK
| | - Marina Abas
- Departamento de Ciencias Marinas y Costeras, Universidad Autónoma de Baja California Sur, La Paz, Baja California Sur, Mexico
| | - Loubna Boutahar
- BioBio Research Center, BioEcoGen Laboratory, Faculty of Sciences, Mohammed V University in Rabat, Rabat, Morocco.,Laboratorío de Biología Marina, Departamento de Zoología, Universidad de Sevilla, Sevilla, Spain
| | - Olivia N Caretti
- Department of Marine, Earth, & Atmospheric Sciences, North Carolina State University, Raleigh, NC, USA
| | - Wing Yan Chan
- Australian Institute of Marine Science, Townsville, QLD, Australia.,School of BioSciences, University of Melbourne, Melbourne, VIC, Australia
| | - Abbie S A Chapman
- School of Ocean and Earth Science, University of Southampton, Southampton, Hampshire, UK.,Centre for Biodiversity and Environment Research, University College London, London, UK
| | | | - Abigail Engleman
- Department of Biological Sciences, Florida State University, Tallahassee, FL, USA
| | - Filippo Ferrario
- Québec-Ocean and Département de Biologie, Université Laval, Québec, QC, Canada
| | - Kayelyn R Simmons
- Department of Marine, Earth, & Atmospheric Sciences, North Carolina State University, Raleigh, NC, USA
| | - Jana Verdura
- Institut d'Ecologia Aquàtica, Facultat de Ciències, Universitat de Girona, Girona, Spain
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30
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Stephenson PJ, Stengel C. An inventory of biodiversity data sources for conservation monitoring. PLoS One 2020; 15:e0242923. [PMID: 33264320 PMCID: PMC7710106 DOI: 10.1371/journal.pone.0242923] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 11/11/2020] [Indexed: 02/08/2023] Open
Abstract
Many conservation managers, policy makers, businesses and local communities cannot access the biodiversity data they need for informed decision-making on natural resource management. A handful of databases are used to monitor indicators against global biodiversity goals but there is no openly available consolidated list of global data sets to help managers, especially those in high-biodiversity countries. We therefore conducted an inventory of global databases of potential use in monitoring biodiversity states, pressures and conservation responses at multiple levels. We uncovered 145 global data sources, as well as a selection of global data reports, links to which we will make available on an open-access website. We describe trends in data availability and actions needed to improve data sharing. If the conservation and science community made a greater effort to publicise data sources, and make the data openly and freely available for the people who most need it, we might be able to mainstream biodiversity data into decision-making and help stop biodiversity loss.
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Affiliation(s)
- P. J. Stephenson
- IUCN SSC Species Monitoring Specialist Group, c/o Laboratory for Conservation Biology, Department of Ecology & Evolution, University of Lausanne, Lausanne, Vaud, Switzerland
| | - Carrie Stengel
- Global Wildlife Conservation, Austin, Texas, United States of America
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31
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Koala Counter: Recording Citizen Scientists’ search paths to Improve Data Quality. Glob Ecol Conserv 2020. [DOI: 10.1016/j.gecco.2020.e01376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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32
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Vimal R, Morgans C. Using knowledge mapping to rethink the gap between science and action. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2020; 34:1433-1443. [PMID: 32506700 DOI: 10.1111/cobi.13563] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 03/19/2020] [Accepted: 03/20/2020] [Indexed: 06/11/2023]
Abstract
Scholars have long stressed the need to bridge the gap between science and action and seek the most efficient use of knowledge for decision making. Many contributors have attempted to consider and understand the sociopolitical forces involved in knowledge generation and exchange. We argue, however, that a model is still needed to adequately conceptualize and frame the knowledge networks in which these processes are embedded. We devised a model for knowledge mapping as a prerequisite for knowledge management in the context of conservation. Using great ape conservation to frame our approach, we propose that knowledge mapping should be based on 2 key principles. First, each conservation network results from the conglomeration of subnetworks of expertise producing and using knowledge. Second, beyond the research-management gradient, other dimensions, such as the scale of operation, geographic location, and organizational characteristics, must also be considered. Assessing both knowledge production and trajectory across different dimensions of the network opens new space for investigating and reducing the gap between science and action.
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Affiliation(s)
- Ruppert Vimal
- GEODE UMR 5602, CNRS, Université Jean-Jaurès, 5 Allée Antonio-Machado, Toulouse, 31058, France
- German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig, 04103, Germany
| | - Courtney Morgans
- Centre for Biodiversity and Conservation Science, School of Biological Sciences, The University of Queensland, Brisbane, QLD, 4072, Australia
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33
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Callaghan CT, Poore AGB, Mesaglio T, Moles AT, Nakagawa S, Roberts C, Rowley JJL, VergÉs A, Wilshire JH, Cornwell WK. Three Frontiers for the Future of Biodiversity Research Using Citizen Science Data. Bioscience 2020. [DOI: 10.1093/biosci/biaa131] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
AbstractCitizen science is fundamentally shifting the future of biodiversity research. But although citizen science observations are contributing an increasingly large proportion of biodiversity data, they only feature in a relatively small percentage of research papers on biodiversity. We provide our perspective on three frontiers of citizen science research, areas that we feel to date have had minimal scientific exploration but that we believe deserve greater attention as they present substantial opportunities for the future of biodiversity research: sampling the undersampled, capitalizing on citizen science's unique ability to sample poorly sampled taxa and regions of the world, reducing taxonomic and spatial biases in global biodiversity data sets; estimating abundance and density in space and time, develop techniques to derive taxon-specific densities from presence or absence and presence-only data; and capitalizing on secondary data collection, moving beyond data on the occurrence of single species and gain further understanding of ecological interactions among species or habitats. The contribution of citizen science to understanding the important biodiversity questions of our time should be more fully realized.
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Affiliation(s)
- Corey T Callaghan
- Centre for Ecosystem Science, School of Biological, Earth, and Environmental Sciences, University of New South Wales
- Ecology and Evolution Research Centre, School of Biological, Earth, and Environmental Sciences, also at the University of New South Wales
| | - Alistair G B Poore
- Ecology and Evolution Research Centre, School of Biological, Earth, and Environmental Sciences, also at the University of New South Wales
| | - Thomas Mesaglio
- Centre for Ecosystem Science, School of Biological, Earth, and Environmental Sciences, University of New South Wales
| | - Angela T Moles
- Ecology and Evolution Research Centre, School of Biological, Earth, and Environmental Sciences, also at the University of New South Wales
| | - Shinichi Nakagawa
- Ecology and Evolution Research Centre, School of Biological, Earth, and Environmental Sciences, also at the University of New South Wales
| | - Christopher Roberts
- Centre for Ecosystem Science, School of Biological, Earth, and Environmental Sciences, University of New South Wales
| | - Jodi J L Rowley
- Australian Museum Research Institute, part of the Australian Museum, Sydney, New South Wales, Australia
| | - Adriana VergÉs
- Ecology and Evolution Research Centre, School of Biological, Earth, and Environmental Sciences, also at the University of New South Wales
| | - John H Wilshire
- Centre for Ecosystem Science, School of Biological, Earth, and Environmental Sciences, University of New South Wales
| | - William K Cornwell
- Centre for Ecosystem Science, School of Biological, Earth, and Environmental Sciences, University of New South Wales
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Rivera-Quiroz FA, Petcharad B, Miller JA. Mining data from legacy taxonomic literature and application for sampling spiders of the Teutamus group (Araneae; Liocranidae) in Southeast Asia. Sci Rep 2020; 10:15787. [PMID: 32978432 PMCID: PMC7519673 DOI: 10.1038/s41598-020-72549-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 09/02/2020] [Indexed: 11/12/2022] Open
Abstract
Taxonomic literature contains information about virtually ever known species on Earth. In many cases, all that is known about a taxon is contained in this kind of literature, particularly for the most diverse and understudied groups. Taxonomic publications in the aggregate have documented a vast amount of specimen data. Among other things, these data constitute evidence of the existence of a particular taxon within a spatial and temporal context. When knowledge about a particular taxonomic group is rudimentary, investigators motivated to contribute new knowledge can use legacy records to guide them in their search for new specimens in the field. However, these legacy data are in the form of unstructured text, making it difficult to extract and analyze without a human interpreter. Here, we used a combination of semi-automatic tools to extract and categorize specimen data from taxonomic literature of one family of ground spiders (Liocranidae). We tested the application of these data on fieldwork optimization, using the relative abundance of adult specimens reported in literature as a proxy to find the best times and places for collecting the species (Teutamus politus) and its relatives (Teutamus group, TG) within Southeast Asia. Based on these analyses we decided to collect in three provinces in Thailand during the months of June and August. With our approach, we were able to collect more specimens of T. politus (188 specimens, 95 adults) than all the previous records in literature combined (102 specimens). Our approach was also effective for sampling other representatives of the TG, yielding at least one representative of every TG genus previously reported for Thailand. In total, our samples contributed 231 specimens (134 adults) to the 351 specimens previously reported in the literature for this country. Our results exemplify one application of mined literature data that allows investigators to more efficiently allocate effort and resources for the study of neglected, endangered, or interesting taxa and geographic areas. Furthermore, the integrative workflow demonstrated here shares specimen data with global online resources like Plazi and GBIF, meaning that others can freely reuse these data and contribute to them in the future. The contributions of the present study represent an increase of more than 35% on the taxonomic coverage of the TG in GBIF based on the number of species. Also, our extracted data represents 72% of the occurrences now available through GBIF for the TG and more than 85% of occurrences of T. politus. Taxonomic literature is a key source of undigitized biodiversity data for taxonomic groups that are underrepresented in the current biodiversity data sphere. Mobilizing these data is key to understanding and protecting some of the less well-known domains of biodiversity.
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Affiliation(s)
- F Andres Rivera-Quiroz
- Department of Terrestrial Zoology, Understanding Evolution group, Naturalis Biodiversity Center, Darwinweg 2, 2333CR, Leiden, The Netherlands.
- Institute of Biology Leiden (IBL), Leiden University, Sylviusweg 72, 2333BE, Leiden, The Netherlands.
| | - Booppa Petcharad
- Faculty of Science and Technology, Thammasat University, Rangsit, 12121, Pathum Thani, Thailand
| | - Jeremy A Miller
- Department of Terrestrial Zoology, Understanding Evolution group, Naturalis Biodiversity Center, Darwinweg 2, 2333CR, Leiden, The Netherlands
- Plazi, Zinggstrasse 16, CH 3007, Bern, Switzerland
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Lindenmayer DB, Lane P, Westgate MJ, Scheele BC, Crane M, Florance D, Crane C, Smith D. Long‐term mammal and nocturnal bird trends are influenced by vegetation type, weather and climate in temperate woodlands. AUSTRAL ECOL 2020. [DOI: 10.1111/aec.12928] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- David B. Lindenmayer
- Sustainable Farms Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory2601 Australia
- Threatened Species Recovery Hub National Environmental Science Program Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory Australia
| | - Peter Lane
- Sustainable Farms Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory2601 Australia
| | - Martin J. Westgate
- Sustainable Farms Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory2601 Australia
| | - Ben C. Scheele
- Threatened Species Recovery Hub National Environmental Science Program Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory Australia
| | - Mason Crane
- Sustainable Farms Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory2601 Australia
| | - Daniel Florance
- Sustainable Farms Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory2601 Australia
- Threatened Species Recovery Hub National Environmental Science Program Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory Australia
| | - Clare Crane
- Sustainable Farms Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory2601 Australia
| | - David Smith
- Sustainable Farms Fenner School of Environment & Society The Australian National University Canberra Australian Capital Territory2601 Australia
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Henckel L, Bradter U, Jönsson M, Isaac NJB, Snäll T. Assessing the usefulness of citizen science data for habitat suitability modelling: Opportunistic reporting versus sampling based on a systematic protocol. DIVERS DISTRIB 2020. [DOI: 10.1111/ddi.13128] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Affiliation(s)
- Laura Henckel
- Swedish Species Information Centre (ArtDatabanken) Swedish University of Agricultural Sciences (SLU) Uppsala Sweden
| | - Ute Bradter
- Swedish Species Information Centre (ArtDatabanken) Swedish University of Agricultural Sciences (SLU) Uppsala Sweden
| | - Mari Jönsson
- Swedish Species Information Centre (ArtDatabanken) Swedish University of Agricultural Sciences (SLU) Uppsala Sweden
| | | | - Tord Snäll
- Swedish Species Information Centre (ArtDatabanken) Swedish University of Agricultural Sciences (SLU) Uppsala Sweden
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Gladstone NS, Bordeau TA, Leppanen C, McKinney ML. Spatiotemporal patterns of non-native terrestrial gastropods in the contiguous United States. NEOBIOTA 2020. [DOI: 10.3897/neobiota.57.52195] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The contiguous United States (CONUS) harbor a significant non-native species diversity. However, spatiotemporal trends of some groups such as terrestrial gastropods (i.e., land snails and slugs) have not been comprehensively considered, and therefore management has been hindered. Here, our aims were to 1.) compile a dataset of all non-native terrestrial gastropod species with CONUS occurrence records, 2.) assess overarching spatiotemporal patterns associated with these records, 3.) describe the continental origin of each species, and 4.) compare climatic associations of each species in their indigenous and introduced CONUS ranges. We compiled a georeferenced dataset of 10,097 records for 22 families, 48 genera, and 69 species, with > 70% of records sourced from the citizen science database iNaturalist. The species Cornu aspersum Müller, 1774 was most prevalent with 3,672 records. The majority (> 92%) of records exhibit an indigenous Western European and Mediterranean distribution, with overlap in broad-scale climatic associations between indigenous and CONUS ranges. Records are most dense in urban metropolitan areas, with the highest proportion of records and species richness in the state of California. We show increased prevalence of non-native species through time, largely associated with urbanized areas with high human population density. Moreover, we show strong evidence for a role for analogous climates in dictating geographic fate and pervasiveness between indigenous and CONUS ranges for non-native species.
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Kays R, McShea WJ, Wikelski M. Born‐digital biodiversity data: Millions and billions. DIVERS DISTRIB 2020. [DOI: 10.1111/ddi.12993] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Roland Kays
- North Carolina Museum of Natural Sciences and North Carolina State University Raleigh NC USA
| | | | - Martin Wikelski
- Department of Migration Max Planck Institute of Animal Behavior Radolfzell Germany
- Centre for the Advanced Study of Collective Behaviour University of Konstanz Radolfzell Germany
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Marshall BM, Strine CT. Exploring snake occurrence records: Spatial biases and marginal gains from accessible social media. PeerJ 2019; 7:e8059. [PMID: 31871833 PMCID: PMC6924322 DOI: 10.7717/peerj.8059] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 10/18/2019] [Indexed: 11/20/2022] Open
Abstract
A species’ distribution provides fundamental information on: climatic niche, biogeography, and conservation status. Species distribution models often use occurrence records from biodiversity databases, subject to spatial and taxonomic biases. Deficiencies in occurrence data can lead to incomplete species distribution estimates. We can incorporate other data sources to supplement occurrence datasets. The general public is creating (via GPS-enabled cameras to photograph wildlife) incidental occurrence records that may present an opportunity to improve species distribution models. We investigated (1) occurrence data of a cryptic group of animals: non-marine snakes, in a biodiversity database (Global Biodiversity Information Facility (GBIF)) and determined (2) whether incidental occurrence records extracted from geo-tagged social media images (Flickr) could improve distribution models for 18 tropical snake species. We provide R code to search for and extract data from images using Flickr’s API. We show the biodiversity database’s 302,386 records disproportionately originate from North America, Europe and Oceania (250,063, 82.7%), with substantial gaps in tropical areas that host the highest snake diversity. North America, Europe and Oceania averaged several hundred records per species; whereas Asia, Africa and South America averaged less than 35 per species. Occurrence density showed similar patterns; Asia, Africa and South America have roughly ten-fold fewer records per 100 km2than other regions. Social media provided 44,687 potential records. However, including them in distribution models only marginally impacted niche estimations; niche overlap indices were consistently over 0.9. Similarly, we show negligible differences in Maxent model performance between models trained using GBIF-only and Flickr-supplemented datasets. Model performance appeared dependent on species, rather than number of occurrences or training dataset. We suggest that for tropical snakes, accessible social media currently fails to deliver appreciable benefits for estimating species distributions; but due to the variation between species and the rapid growth in social media data, may still be worth considering in future contexts.
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Affiliation(s)
- Benjamin M Marshall
- School of Biology, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, Nakhon Ratchasima, Thailand
| | - Colin T Strine
- School of Biology, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, Nakhon Ratchasima, Thailand
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Isaac NJB, Jarzyna MA, Keil P, Dambly LI, Boersch-Supan PH, Browning E, Freeman SN, Golding N, Guillera-Arroita G, Henrys PA, Jarvis S, Lahoz-Monfort J, Pagel J, Pescott OL, Schmucki R, Simmonds EG, O'Hara RB. Data Integration for Large-Scale Models of Species Distributions. Trends Ecol Evol 2019; 35:56-67. [PMID: 31676190 DOI: 10.1016/j.tree.2019.08.006] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 08/08/2019] [Accepted: 08/12/2019] [Indexed: 01/23/2023]
Abstract
With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise.
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Affiliation(s)
- Nick J B Isaac
- Centre for Ecology and Hydrology, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK; Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK.
| | - Marta A Jarzyna
- Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Petr Keil
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, 04103 Leipzig, Germany; Institute of Computer Science, Martin Luther University Halle-Wittenberg, 06120, Halle (Saale), Germany
| | - Lea I Dambly
- Centre for Ecology and Hydrology, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK; Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Philipp H Boersch-Supan
- British Trust for Ornithology, Thetford, IP24 2PU, UK; Department of Geography, University of Florida, Gainesville, FL 32611, USA
| | - Ella Browning
- Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK; Institute of Zoology, Zoological Society of London, London, NW1 4RY, UK
| | - Stephen N Freeman
- Centre for Ecology and Hydrology, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Nick Golding
- School of BioSciences, University of Melbourne, Parkville, VIC 3010, Australia
| | | | - Peter A Henrys
- Centre for Ecology and Hydrology, Bailrigg, Lancaster, LA1 4AP, UK
| | - Susan Jarvis
- Centre for Ecology and Hydrology, Bailrigg, Lancaster, LA1 4AP, UK
| | - José Lahoz-Monfort
- School of BioSciences, University of Melbourne, Parkville, VIC 3010, Australia
| | - Jörn Pagel
- Institute of Landscape and Plant Ecology, University of Hohenheim, 70599 Stuttgart, Germany
| | - Oliver L Pescott
- Centre for Ecology and Hydrology, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Reto Schmucki
- Centre for Ecology and Hydrology, Benson Lane, Crowmarsh Gifford, Wallingford, OX10 8BB, UK
| | - Emily G Simmonds
- Department of Mathematical Sciences, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
| | - Robert B O'Hara
- Department of Mathematical Sciences, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
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41
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Yletyinen J, Brown P, Pech R, Hodges D, Hulme PE, Malcolm TF, Maseyk FJF, Peltzer DA, Perry GLW, Richardson SJ, Smaill SJ, Stanley MC, Todd JH, Walsh PJ, Wright W, Tylianakis JM. Understanding and Managing Social–Ecological Tipping Points in Primary Industries. Bioscience 2019. [DOI: 10.1093/biosci/biz031] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Johanna Yletyinen
- School of Biological Sciences, University of Canterbury in Christchurch, New Zealand
- Manaaki Whenua Landcare Research Ltd. branches in Lincoln, Wellington and Auckland, in New Zealand
| | - Philip Brown
- Manaaki Whenua Landcare Research Ltd. branches in Lincoln, Wellington and Auckland, in New Zealand
| | - Roger Pech
- Manaaki Whenua Landcare Research Ltd. branches in Lincoln, Wellington and Auckland, in New Zealand
| | | | - Philip E Hulme
- Bio-Protection Research Centre at Lincoln University, New Zealand
| | | | - Fleur J F Maseyk
- The Catalyst Group, in Wellington, New Zealand, and with the Centre for Biodiversity and Conservation Science at the University of Queensland in Brisbane, Australia
| | - Duane A Peltzer
- Manaaki Whenua Landcare Research Ltd. branches in Lincoln, Wellington and Auckland, in New Zealand
| | - George L W Perry
- School of Environment at the University of Auckland, New Zealand
| | - Sarah J Richardson
- Manaaki Whenua Landcare Research Ltd. branches in Lincoln, Wellington and Auckland, in New Zealand
| | | | - Margaret C Stanley
- School of Biological Sciences, at the University of Auckland, New Zealand
| | - Jacqui H Todd
- The New Zealand Institute for Plant and Food Research, Ltd., in Auckland, and Willie Wright is affiliated with the Integrated Kaipara Harbour Management Group, in Whangarei, New Zealand
| | - Patrick J Walsh
- Manaaki Whenua Landcare Research Ltd. branches in Lincoln, Wellington and Auckland, in New Zealand
| | - Willie Wright
- School of Biological Sciences, University of Canterbury in Christchurch, New Zealand
| | - Jason M Tylianakis
- School of Biological Sciences, University of Canterbury in Christchurch, New Zealand
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