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Lucas PM, Di Marco M, Cazalis V, Luedtke J, Neam K, Brown MH, Langhammer PF, Mancini G, Santini L. Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024:e14316. [PMID: 38946355 DOI: 10.1111/cobi.14316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 07/02/2024]
Abstract
Assessing the extinction risk of species based on the International Union for Conservation of Nature (IUCN) Red List (RL) is key to guiding conservation policies and reducing biodiversity loss. This process is resource demanding, however, and requires continuous updating, which becomes increasingly difficult as new species are added to the RL. Automatic methods, such as comparative analyses used to predict species RL category, can be an efficient alternative to keep assessments up to date. Using amphibians as a study group, we predicted which species are more likely to change their RL category and thus should be prioritized for reassessment. We used species biological traits, environmental variables, and proxies of climate and land-use change as predictors of RL category. We produced an ensemble prediction of IUCN RL category for each species by combining 4 different model algorithms: cumulative link models, phylogenetic generalized least squares, random forests, and neural networks. By comparing RL categories with the ensemble prediction and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessment based on the mismatch between predicted and observed values. The most important predicting variables across models were species' range size and spatial configuration of the range, biological traits, climate change, and land-use change. We compared our proposed prioritization index and the predicted RL changes with independent IUCN RL reassessments and found high performance of both the prioritization and the predicted directionality of changes in RL categories. Ensemble modeling of RL category is a promising tool for prioritizing species for reassessment while accounting for models' uncertainty. This approach is broadly applicable to all taxa on the IUCN RL and to regional and national assessments and may improve allocation of the limited human and economic resources available to maintain an up-to-date IUCN RL.
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Affiliation(s)
- Pablo Miguel Lucas
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
- Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Sevilla, Spain
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - Jennifer Luedtke
- IUCN SSC Amphibian Specialist Group, Toronto, Ontario, Canada
- Re:wild, Austin, Texas, USA
| | - Kelsey Neam
- IUCN SSC Amphibian Specialist Group, Toronto, Ontario, Canada
- Re:wild, Austin, Texas, USA
| | | | | | - Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
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2
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Bachman SP, Brown MJM, Leão TCC, Nic Lughadha E, Walker BE. Extinction risk predictions for the world's flowering plants to support their conservation. THE NEW PHYTOLOGIST 2024; 242:797-808. [PMID: 38437880 DOI: 10.1111/nph.19592] [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: 12/21/2022] [Accepted: 01/23/2024] [Indexed: 03/06/2024]
Abstract
More than 70% of all vascular plants lack conservation status assessments. We aimed to address this shortfall in knowledge of species extinction risk by using the World Checklist of Vascular Plants to generate the first comprehensive set of predictions for a large clade: angiosperms (flowering plants, c. 330 000 species). We used Bayesian Additive Regression Trees (BART) to predict the extinction risk of all angiosperms using predictors relating to range size, human footprint, climate, and evolutionary history and applied a novel approach to estimate uncertainty of individual species-level predictions. From our model predictions, we estimate 45.1% of angiosperm species are potentially threatened with a lower bound of 44.5% and upper bound of 45.7%. Our species-level predictions, with associated uncertainty estimates, do not replace full global, or regional Red List assessments, but can be used to prioritise predicted threatened species for full Red List assessment and fast-track predicted non-threatened species for Least Concern assessments. Our predictions and uncertainty estimates can also guide fieldwork, inform systematic conservation planning and support global plant conservation efforts and targets.
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3
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Boonman CCF, Serra-Diaz JM, Hoeks S, Guo WY, Enquist BJ, Maitner B, Malhi Y, Merow C, Buitenwerf R, Svenning JC. More than 17,000 tree species are at risk from rapid global change. Nat Commun 2024; 15:166. [PMID: 38167693 PMCID: PMC10761716 DOI: 10.1038/s41467-023-44321-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 12/08/2023] [Indexed: 01/05/2024] Open
Abstract
Trees are pivotal to global biodiversity and nature's contributions to people, yet accelerating global changes threaten global tree diversity, making accurate species extinction risk assessments necessary. To identify species that require expert-based re-evaluation, we assess exposure to change in six anthropogenic threats over the last two decades for 32,090 tree species. We estimated that over half (54.2%) of the assessed species have been exposed to increasing threats. Only 8.7% of these species are considered threatened by the IUCN Red List, whereas they include more than half of the Data Deficient species (57.8%). These findings suggest a substantial underestimation of threats and associated extinction risk for tree species in current assessments. We also map hotspots of tree species exposed to rapidly changing threats around the world. Our data-driven approach can strengthen the efforts going into expert-based IUCN Red List assessments by facilitating prioritization among species for re-evaluation, allowing for more efficient conservation efforts.
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Affiliation(s)
- Coline C F Boonman
- Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) & Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus, Denmark.
| | - Josep M Serra-Diaz
- Department of Ecology and Evolution and Eversource Energy Center, University of Connecticut, Storrs, CT, USA
- Université de Lorraine, AgroParisTech, INRAE, Silva, Nancy, France
| | - Selwyn Hoeks
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, The Netherlands
| | - Wen-Yong Guo
- Research Center for Global Change and Complex Ecosystems, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, 200241, People's Republic of China
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, 200241, People's Republic of China
| | - Brian J Enquist
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA
| | - Brian Maitner
- Department of Geography, University at Buffalo, Buffalo, NY, USA
| | - Yadvinder Malhi
- Environmental Change Institute, School of Geography and the Environment, University of Oxford, South Parks Road, Oxford, OX1 3QY, England, UK
- Leverhulme Centre for Nature Recovery, University of Oxford, Oxford, UK
| | - Cory Merow
- Department of Ecology and Evolution and Eversource Energy Center, University of Connecticut, Storrs, CT, USA
| | - Robert Buitenwerf
- Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) & Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus, Denmark
| | - Jens-Christian Svenning
- Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) & Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus, Denmark
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4
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Brown MJM, Walker BE, Budden AP, Nic Lughadha E. Re-evaluating the importance of threatened species in maintaining global phytoregions. THE NEW PHYTOLOGIST 2023; 240:1673-1686. [PMID: 37798820 DOI: 10.1111/nph.19295] [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: 12/14/2022] [Accepted: 09/05/2023] [Indexed: 10/07/2023]
Abstract
Anthropogenic introductions are known to be changing the structure of global phytogeographical regions (phytoregions), but previous studies have been limited by incomplete or biased data sets that are likely to underestimate the importance of threatened species. In this work, we analyse a comprehensive data set of all known species and their occurrences (at botanical country resolution) to quantify the impact of potential future extinction scenarios. We used Infomap, a network-based community detection algorithm, to generate phytoregional delineations for six species-distribution scenarios (native, introduced and extinctions of species that are either documented as threatened or likely to be threatened, as well as combinations thereof). We compared the numbers and sizes of phytoregions to characterise the amount and spatial distribution of changes in global phytoregions under each scenario. Extinctions of species that are predicted to be threatened had a greater homogenising effect on phytoregions than introductions, and there was some evidence that introductions may even mitigate the homogenisation caused by extinctions, though this interaction is complex. This research provides the first evidence that the loss of threatened species would have significant ramifications for global phytoregions and demonstrates the need to consider extinction processes in studies of anthropogenic effects on biodiversity patterns.
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5
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Antonelli A, Govaerts R, Nic Lughadha E, Onstein RE, Smith RJ, Zizka A. Why plant diversity and distribution matter. THE NEW PHYTOLOGIST 2023; 240:1331-1336. [PMID: 37813121 DOI: 10.1111/nph.19282] [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: 09/08/2023] [Accepted: 09/08/2023] [Indexed: 10/11/2023]
Abstract
This article is the Editorial for the Special Collection ‘Global plant diversity and distribution’. See https://www.newphytologist.org/global-plant-diversity for more details.
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Affiliation(s)
- Alexandre Antonelli
- Royal Botanic Gardens, Kew, Richmond, TW9 3AE, UK
- Department of Biological and Environmental Sciences, Gothenburg Global Biodiversity Centre, University of Gothenburg, Box 461, Gothenburg, SE 405 30, Sweden
- Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China
- Department of Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
| | | | | | - Renske E Onstein
- Naturalis Biodiversity Center, Darwinweg 2, Leiden, 2333CR, the Netherlands
- German Center for Integrative Biodiversity Research (iDiv) Halle - Jena - Leipzig, Puschstrasse 4, Leipzig, 04103, Germany
| | | | - Alexander Zizka
- Naturalis Biodiversity Center, Darwinweg 2, Leiden, 2333CR, the Netherlands
- Department of Biology, Philipps University Marburg, Karl-von-Frisch-Straße 8, Marburg, 35043, Germany
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6
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Swati U, D'Souza S, Aravind PS, Muni RK, Rajamani N. A comprehensive database of squirrel distribution and occurrence in South Asia. Biodivers Data J 2023; 11:e109946. [PMID: 38312334 PMCID: PMC10838086 DOI: 10.3897/bdj.11.e109946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 10/19/2023] [Indexed: 02/06/2024] Open
Abstract
Background The Squirrels of South Asia (SOSA) database compiles comprehensive distribution and occurrence information on all squirrel species that occur in this region (34 species). These 34 squirrel species, including tree, flying and ground squirrels, represent 14% of global sciurid diversity. The database collates curated data from various sources such as museums, literature, primary fieldwork, citizen science and social media platforms and covers the entire distributional ranges of the target species, including countries in Central Asia and Southeast Asia when required. The SOSA database enhances our understanding of squirrel distribution, population dynamics and their conservation needs in South Asia by consolidating information. It aims to be a valuable resource for researchers, conservationists and wildlife enthusiasts. New information As of March 2023, the database comprises over 40,000 records of 34 species in over 30 countries globally. Spending an average of 334 hours on each species, more than 20 data collectors put in over 10,000 hours to gather, curate and build this database. The database has resulted in novel records of species occurrence in regions and countries that are poorly represented in currently available global data repositories. The current version which has been made public via GBIF comprises of 1187 records of all 34 species across multiple sources. This is a subset of the SOSA database.
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Affiliation(s)
- Udayraj Swati
- IISER Tirupati, Tirupati, IndiaIISER TirupatiTirupatiIndia
| | - Senan D'Souza
- IISER Tirupati, Tirupati, IndiaIISER TirupatiTirupatiIndia
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7
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Daru BH, Rodriguez J. Mass production of unvouchered records fails to represent global biodiversity patterns. Nat Ecol Evol 2023:10.1038/s41559-023-02047-3. [PMID: 37127769 DOI: 10.1038/s41559-023-02047-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 03/26/2023] [Indexed: 05/03/2023]
Abstract
The ever-increasing human footprint even in very remote places on Earth has inspired efforts to document biodiversity vigorously in case organisms go extinct. However, the data commonly gathered come from either primary voucher specimens in a natural history collection or from direct field observations that are not traceable to tangible material in a museum or herbarium. Although both datasets are crucial for assessing how anthropogenic drivers affect biodiversity, they have widespread coverage gaps and biases that may render them inefficient in representing patterns of biodiversity. Using a large global dataset of around 1.9 billion occurrence records of terrestrial plants, butterflies, amphibians, birds, reptiles and mammals, we quantify coverage and biases of expected biodiversity patterns by voucher and observation records. We show that the mass production of observation records does not lead to higher coverage of expected biodiversity patterns but is disproportionately biased toward certain regions, clades, functional traits and time periods. Such coverage patterns are driven by the ease of accessibility to air and ground transportation, level of security and extent of human modification at each sampling site. Conversely, voucher records are vastly infrequent in occurrence data but in the few places where they are sampled, showed relative congruence with expected biodiversity patterns for all dimensions. The differences in coverage and bias by voucher and observation records have important implications on the utility of these records for research in ecology, evolution and conservation research.
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Affiliation(s)
- Barnabas H Daru
- Department of Biology, Stanford University, Stanford, CA, USA.
| | - Jordan Rodriguez
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR, USA
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8
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Nguyen T, Malina R, Mokas I, Papakonstantinou A, Polyzos O, Vanhove MPM. WASP: the World Archives of Species Perception. Database (Oxford) 2023; 2023:7059526. [PMID: 36852842 PMCID: PMC9972524 DOI: 10.1093/database/baad003] [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: 10/19/2022] [Revised: 01/04/2023] [Accepted: 02/02/2023] [Indexed: 03/01/2023]
Abstract
While human perception can play a role in influencing public support for species conservation, the mechanisms underlying human perception remain poorly understood. Some previous studies on perception have focused on a few specific taxa, which makes the understanding of the public perception of species at large a resource- and time-intensive task. Here, we introduce the World Archives of Species Perception project that consists of an animal survey and a plant survey to construct the first systematic database to study the human perception of the floral and faunal diversity at a global scale. We provide a description of our survey method, species selection, survey implementation and a discussion of the potential uses of our databases in multidisciplinary research. In the animal survey, we cover 1980 International Union for Conservation of Nature (IUCN)-evaluated species, representing 25 classes, 192 orders, 1037 families and 1705 genera. In the plant survey, we cover 2000 IUCN-evaluated species, representing 13 classes, 93 orders, 386 families and 1968 genera. Data from the survey will be collected and made available 24 months after the publication of the article. Database URL http://wasp-project.net/.
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Affiliation(s)
| | - Robert Malina
- Research Group Environmental Economics, Centre for Environmental Sciences, Hasselt University, Martelarenlaan 42, Hasselt 3500, Belgium
| | - Ilias Mokas
- Research Group Environmental Economics, Centre for Environmental Sciences, Hasselt University, Martelarenlaan 42, Hasselt 3500, Belgium
| | | | | | - Maarten P M Vanhove
- Research Group Zoology, Biodiversity and Toxicology, Centre for Environmental Sciences, Hasselt University, Agoralaan gebouw D, Diepenbeek 3590, Belgium
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9
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Walker BE, Leão TCC, Bachman SP, Lucas E, Nic Lughadha E. Evidence-based guidelines for automated conservation assessments of plant species. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2023; 37:e13992. [PMID: 36047690 PMCID: PMC10092660 DOI: 10.1111/cobi.13992] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 06/30/2022] [Accepted: 08/01/2022] [Indexed: 05/22/2023]
Abstract
Assessing species' extinction risk is vital to setting conservation priorities. However, assessment endeavors, such as those used to produce the IUCN Red List of Threatened Species, have significant gaps in taxonomic coverage. Automated assessment (AA) methods are gaining popularity to fill these gaps. Choices made in developing, using, and reporting results of AA methods could hinder their successful adoption or lead to poor allocation of conservation resources. We explored how choice of data cleaning type and level, taxonomic group, training sample, and automation method affect performance of threat status predictions for plant species. We used occurrences from the Global Biodiversity Information Facility (GBIF) to generate assessments for species in 3 taxonomic groups based on 6 different occurrence-based AA methods. We measured each method's performance and coverage following increasingly stringent occurrence cleaning. Automatically cleaned data from GBIF performed comparably to occurrence records cleaned manually by experts. However, all types of data cleaning limited the coverage of AAs. Overall, machine-learning-based methods performed well across taxa, even with minimal data cleaning. Results suggest a machine-learning-based method applied to minimally cleaned data offers the best compromise between performance and species coverage. However, optimal data cleaning, training sample, and automation methods depend on the study group, intended applications, and expertise.
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Affiliation(s)
| | | | | | - Eve Lucas
- Royal Botanic GardensKewRichmond, Surrey, TW9 3AEUK
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10
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Marshall CAM, Dabo J, Mensah M, Ekpe P, Hawthorne WD. Implications for conservation assessment from flux in the botanical record over 20 years in southwest Ghana. Ecol Evol 2023; 13:e9775. [PMID: 36713481 PMCID: PMC9873867 DOI: 10.1002/ece3.9775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 01/05/2023] [Accepted: 01/11/2023] [Indexed: 01/26/2023] Open
Abstract
At best, conservation decisions can only be made using the data available at the time. For plants and especially in the tropics, natural history collections remain the best available baseline information upon which to base conservation assessments, in spite of well-documented limitations in their taxonomic, geographic, and temporal coverage. We explore the extent to which changes to the plant biological record over 20 years have changed our conception of the conservation importance of 931 plant taxa, and 114 vegetation samples, recorded in forest reserves of the southwest Ghana biodiversity hotspot. 36% of species-level assessments changed as a result of new distribution data. 12% of species accepted in 2016 had no assessment in 1996: of those, 20% are new species publications, 60% are new records for SW Ghana, and 20% are taxonomic resolutions. Apparent species ranges have increased over time as new records are made, but new species publications are overwhelmingly of globally rare species, keeping the balance of perceived rarity in the flora constant over 20 years. Thus, in spite of considerable flux at the species record level, range size rarity scores calculated for 114 vegetation samples of the reserves in 1996 and 2016 are highly correlated with each other: r(112) = 0.84, p < .0005, and showed no difference in mean score over 20 years: paired t(113) = -0.482, p = .631. This consistency in results at the area level allows for worthwhile conservation priority setting over time, and we argue is the better course of action than taking no action at all.
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Affiliation(s)
| | | | | | - Patrick Ekpe
- Ghana Herbarium, Department of Plant & Environmental BiologyUniversity of GhanaLegonGhana
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11
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Pironon S, Cantwell-Jones A, Forest F, Ball J, Diazgranados M, Douglas R, Hawkins J, Howes MJR, Ulian T, Vaitla B, Collar D. Towards an action plan for characterizing food plant diversity. NATURE PLANTS 2023; 9:34-35. [PMID: 36543935 DOI: 10.1038/s41477-022-01300-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 10/31/2022] [Indexed: 06/17/2023]
Affiliation(s)
- S Pironon
- Royal Botanic Gardens, Kew, Richmond, UK.
- UN Environment Programme World Conservation Monitoring Centre, Cambridge, UK.
| | - A Cantwell-Jones
- Science and Solutions for a Changing Planet DTP, Imperial College London, Ascot, UK
- Department of Life Sciences, Imperial College London, Ascot, UK
| | - F Forest
- Royal Botanic Gardens, Kew, Richmond, UK
| | - J Ball
- Royal Botanic Gardens, Kew, Richmond, UK
| | | | | | - J Hawkins
- School of Biological Sciences, University of Reading, Reading, UK
| | | | - T Ulian
- Royal Botanic Gardens, Kew, Richmond, UK
| | - B Vaitla
- Department of Nutrition, Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA
| | - D Collar
- Department of Organismal and Environmental Biology, Christopher Newport University, Newport News, VA, USA
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12
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Pelletier TA, Parsons DJ, Decker SK, Crouch S, Franz E, Ohrstrom J, Carstens BC. phylogatR: Phylogeographic data aggregation and repurposing. Mol Ecol Resour 2022; 22:2830-2842. [PMID: 35748425 PMCID: PMC9796472 DOI: 10.1111/1755-0998.13673] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 03/10/2022] [Accepted: 06/07/2022] [Indexed: 01/01/2023]
Abstract
Patterns of genetic diversity within species contain information the history of that species, including how they have responded to historical climate change and how easily the organism is able to disperse across its habitat. More than 40,000 phylogeographic and population genetic investigations have been published to date, each collecting genetic data from hundreds of samples. Despite these millions of data points, meta-analyses are challenging because the synthesis of results across hundreds of studies, each using different methods and forms of analysis, is a daunting and time-consuming task. It is more efficient to proceed by repurposing existing data and using automated data analysis. To facilitate data repurposing, we created a database (phylogatR) that aggregates data from different sources and conducts automated multiple sequence alignments and data curation to provide users with nearly ready-to-analyse sets of data for thousands of species. Two types of scientific research will be made easier by phylogatR: large meta-analyses of thousands of species that can address classic questions in evolutionary biology and ecology, and student- or citizen- science based investigations that will introduce a broad range of people to the analysis of genetic data. phylogatR enhances the value of existing data via the creation of software and web-based tools that enable these data to be recycled and reanalysed and increase accessibility to big data for research laboratories and classroom instructors with limited computational expertise and resources.
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Affiliation(s)
| | - Danielle J. Parsons
- Department of Evolution, Ecology, and Organismal BiologyThe Ohio State UniversityColumbusOhioUSA,Museum of Biological DiversityThe Ohio State UniversityColumbusOhioUSA
| | - Sydney K. Decker
- Department of Evolution, Ecology, and Organismal BiologyThe Ohio State UniversityColumbusOhioUSA,Museum of Biological DiversityThe Ohio State UniversityColumbusOhioUSA
| | | | - Eric Franz
- Ohio Supercomputer CenterColumbusOhioUSA
| | | | - Bryan C. Carstens
- Department of Evolution, Ecology, and Organismal BiologyThe Ohio State UniversityColumbusOhioUSA,Museum of Biological DiversityThe Ohio State UniversityColumbusOhioUSA
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13
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The likely extinction of hundreds of palm species threatens their contributions to people and ecosystems. Nat Ecol Evol 2022; 6:1710-1722. [PMID: 36163257 DOI: 10.1038/s41559-022-01858-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 07/24/2022] [Indexed: 02/07/2023]
Abstract
Protecting nature's contributions to people requires accelerating extinction risk assessment and better integrating evolutionary, functional and used diversity with conservation planning. Here, we report machine learning extinction risk predictions for 1,381 palm species (Arecaceae), a plant family of high socio-economic and ecological importance. We integrate these predictions with published assessments for 508 species (covering 75% of all palm species) and we identify top-priority regions for palm conservation on the basis of their proportion of threatened evolutionarily distinct, functionally distinct and used species. Finally, we explore palm use resilience to identify non-threatened species that could potentially serve as substitutes for threatened used species by providing similar products. We estimate that over a thousand palms (56%) are probably threatened, including 185 species with documented uses. Some regions (New Guinea, Vanuatu and Vietnam) emerge as top ten priorities for conservation only after incorporating machine learning extinction risk predictions. Potential substitutes are identified for 91% of the threatened used species and regional use resilience increases with total palm richness. However, 16 threatened used species lack potential substitutes and 30 regions lack substitutes for at least one of their threatened used palm species. Overall, we show that hundreds of species of this keystone family face extinction, some of them probably irreplaceable, at least locally. This highlights the need for urgent actions to avoid major repercussions on palm-associated ecosystem processes and human livelihoods in the coming decades.
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14
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Gaisberger H, Fremout T, Kettle CJ, Vinceti B, Kemalasari D, Kanchanarak T, Thomas E, Serra-Diaz JM, Svenning JC, Slik F, Eiadthong W, Palanisamy K, Ravikanth G, Bodos V, Sang J, Warrier RR, Wee AKS, Elloran C, Ramos LT, Henry M, Hossain MA, Theilade I, Laegaard S, Bandara KMA, Weerasinghe DP, Changtragoon S, Yuskianti V, Wilkie P, Nghia NH, Elliott S, Pakkad G, Tiansawat P, Maycock C, Bounithiphonh C, Mohamed R, Nazre M, Siddiqui BN, Lee SL, Lee CT, Zakaria NF, Hartvig I, Lehmann L, David DBD, Lillesø JPB, Phourin C, Yongqi Z, Ping H, Volkaert HA, Graudal L, Hamidi A, Thea S, Sreng S, Boshier D, Tolentino E, Ratnam W, Aung MM, Galante M, Isa SFM, Dung NQ, Hoa TT, Le TC, Miah MD, Zuhry ALM, Alawathugoda D, Azman A, Pushpakumara G, Sumedi N, Siregar IZ, Nak HK, Linsky J, Barstow M, Koh LP, Jalonen R. Tropical and subtropical Asia's valued tree species under threat. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2022; 36:e13873. [PMID: 34865262 DOI: 10.1111/cobi.13873] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/14/2021] [Accepted: 11/25/2021] [Indexed: 06/13/2023]
Abstract
Tree diversity in Asia's tropical and subtropical forests is central to nature-based solutions. Species vulnerability to multiple threats, which affect provision of ecosystem services, is poorly understood. We conducted a region-wide, spatially explicit assessment of the vulnerability of 63 socioeconomically important tree species to overexploitation, fire, overgrazing, habitat conversion, and climate change. Trees were selected for assessment from national priority lists, and selections were validated by an expert network representing 20 countries. We used Maxent suitability modeling to predict species distribution ranges, freely accessible spatial data sets to map threat exposures, and functional traits to estimate threat sensitivities. Species-specific vulnerability maps were created as the product of exposure maps and sensitivity estimates. Based on vulnerability to current threats and climate change, we identified priority areas for conservation and restoration. Overall, 74% of the most important areas for conservation of these trees fell outside protected areas, and all species were severely threatened across an average of 47% of their native ranges. The most imminent threats were overexploitation and habitat conversion; populations were severely threatened by these factors in an average of 24% and 16% of their ranges, respectively. Our model predicted limited overall climate change impacts, although some study species were likely to lose over 15% of their habitat by 2050 due to climate change. We pinpointed specific natural areas in Borneo rain forests as hotspots for in situ conservation of forest genetic resources, more than 82% of which fell outside designated protected areas. We also identified degraded areas in Western Ghats, Indochina dry forests, and Sumatran rain forests as hotspots for restoration, where planting or assisted natural regeneration will help conserve these species, and croplands in southern India and Thailand as potentially important agroforestry options. Our results highlight the need for regionally coordinated action for effective conservation and restoration.
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Affiliation(s)
- Hannes Gaisberger
- Bioversity International, Rome, Italy
- Department of Geoinformatics, Paris Lodron University of Salzburg, Salzburg, Austria
| | - Tobias Fremout
- Division of Forest, Nature and Landscape, KU Leuven, Leuven-Heverlee, Belgium
- Bioversity International, La Molina, Peru
| | - Chris J Kettle
- Bioversity International, Rome, Italy
- Department of Environmental System Science, ETH Zurich, Zurich, Switzerland
| | | | - Della Kemalasari
- Bioversity International, Universiti Putra Malaysia Off Lebuh Silikon, Selangor, Malaysia
| | - Tania Kanchanarak
- Bioversity International, Universiti Putra Malaysia Off Lebuh Silikon, Selangor, Malaysia
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | | | | | - Jens-Christian Svenning
- Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus C, Denmark
| | - Ferry Slik
- Universiti Brunei Darussalam, Jalan Tungku Link, Gadong, Brunei Darussalam
| | | | | | | | - Vilma Bodos
- Forest Department Sarawak, Bangunan Baitul Makmur II, Kuching, Malaysia
| | - Julia Sang
- Forest Department Sarawak, Bangunan Baitul Makmur II, Kuching, Malaysia
| | - Rekha R Warrier
- Institute of Forest Genetics and Tree Breeding, Tamil Nadu, India
| | - Alison K S Wee
- School of Environmental and Geographical Sciences, University of Nottingham Malaysia Campus, Semenyih, Malaysia
- Selangor Darul Ehsan, Malaysia and College of Forestry, Guangxi University, Nanning, People's Republic of China
| | | | | | - Matieu Henry
- Food and Agriculture Organization of the United Nations (FAO), Dhaka, Bangladesh
| | - Md Akhter Hossain
- Institute of Forestry and Environmental Sciences, University of Chittagong, Chittagong, Bangladesh
| | - Ida Theilade
- Department of Food and Resource Economics, University of Copenhagen, Frederiksberg C, Denmark
| | | | - K M A Bandara
- Sri Lanka Forestry Institute, Nuwara Eliya, Sri Lanka
| | | | | | - Vivi Yuskianti
- Forest Research and Development Center (FRDC), Bogor, Indonesia
| | | | | | - Stephen Elliott
- Forest Restoration Research Unit, Biology Department and Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Greuk Pakkad
- Forest Restoration Research Unit, Biology Department and Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Pimonrat Tiansawat
- Forest Restoration Research Unit, Biology Department and Environmental Science Research Centre, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
| | - Colin Maycock
- Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, Malaysia
| | - Chaloun Bounithiphonh
- Forest Research Center, National Agriculture and Forestry Research Institute, Xaythany District, Lao P.D.R
| | - Rozi Mohamed
- Faculty of Forestry & Environment, Universiti Putra Malaysia, UPM Serdang, Malaysia
| | - M Nazre
- Faculty of Forestry & Environment, Universiti Putra Malaysia, UPM Serdang, Malaysia
| | | | - Soon-Leong Lee
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | - Chai-Ting Lee
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | - Nurul Farhanah Zakaria
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | - Ida Hartvig
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Smithsonian Environmental Research Center, Smithsonian Institute, Washington, DC, USA
| | - Lutz Lehmann
- Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Bonn, Germany
| | | | | | - Chhang Phourin
- Institute of Forest and Wildlife Research and Development, Khan Sen Sokh, Cambodia
| | - Zheng Yongqi
- Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Huang Ping
- Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Hugo A Volkaert
- Center for Agricultural Biotechnology, Kasetsart University Kamphaengsaen Campus, Mu6 Malaimaen Rd, Kamphaengsaen Nakhonpathom 73140, Thailand, Lat Yao, Thailand
| | - Lars Graudal
- Department of Food and Resource Economics, University of Copenhagen, Frederiksberg C, Denmark
- World Agroforestry Center (ICRAF), United Nations Avenue, Nairobi, Kenya
| | - Arief Hamidi
- Fauna and Flora International, Nusa Tenggara, Indonesia
| | - So Thea
- Institute of Forest and Wildlife Research and Development, Khan Sen Sokh, Cambodia
| | - Sineath Sreng
- Institute of Forest and Wildlife Research and Development, Khan Sen Sokh, Cambodia
| | | | - Enrique Tolentino
- University of the Philippines Los Baños, College, Laguna 4031, Philippines, Los Baños, Philippines
| | | | - Mu Mu Aung
- Forest Department Myanmar, Mon State, Myanmar
| | - Michael Galante
- Climate Forestry Limited, Kensington Gardens, Labuan, Malaysia
| | - Siti Fatimah Md Isa
- Department of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang, Malaysia
| | - Nguyen Quoc Dung
- Forest Inventory and Planning Institute, Quy hoạch Rừng, Vietnam
| | - Tran Thi Hoa
- Institute of Agricultural Genetics (AGI), Forest Genetics and Conservation, Vietnamese Academy of Agricultural Sciences, Hanoi, Vietnam
| | - Tran Chan Le
- Institute of Agricultural Genetics (AGI), Forest Genetics and Conservation, Vietnamese Academy of Agricultural Sciences, Hanoi, Vietnam
| | | | | | | | - Amelia Azman
- Forest Research Institute Malaysia, Jalan Frim, Institut Penyelidikan Perhutanan Malaysia, Kuala Lumpur, Malaysia
| | | | - Nur Sumedi
- Forest Research and Development Center (FRDC), Bogor, Indonesia
| | | | - Hong Kyung Nak
- Forest Bioinformation Division, National Institute of Forest Science (NIFOS), Seoul, Republic of Korea
| | - Jean Linsky
- Atlanta Botanical Garden, Atlanta, Georgia, USA
| | - Megan Barstow
- Botanic Gardens Conservation International, Richmond, UK
| | - Lian Pin Koh
- Centre for Nature-based Climate Solutions, and Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Riina Jalonen
- Bioversity International, Universiti Putra Malaysia Off Lebuh Silikon, Selangor, Malaysia
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15
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Caetano GHDO, Chapple DG, Grenyer R, Raz T, Rosenblatt J, Tingley R, Böhm M, Meiri S, Roll U. Automated assessment reveals that the extinction risk of reptiles is widely underestimated across space and phylogeny. PLoS Biol 2022; 20:e3001544. [PMID: 35617356 PMCID: PMC9135251 DOI: 10.1371/journal.pbio.3001544] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 04/21/2022] [Indexed: 11/19/2022] Open
Abstract
The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision-making. However, despite substantial effort, numerous species remain unassessed or have insufficient data available to be assigned a Red List extinction risk category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here, we aimed to (1) present a machine learning–based automated extinction risk assessment method that can be used on less known species; (2) offer provisional assessments for all reptiles—the only major tetrapod group without a comprehensive Red List assessment; and (3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. The models used in our predictions were 90% accurate in classifying species as threatened/nonthreatened, and 84% accurate in predicting specific extinction risk categories. Unassessed and Data Deficient reptiles were considerably more likely to be threatened than assessed species, adding to mounting evidence that these species warrant more conservation attention. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap for other less known taxa.
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Affiliation(s)
- Gabriel Henrique de Oliveira Caetano
- Jacob Blaustein Center for Scientific Cooperation, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
- Mitrani Department of Desert Ecology, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
| | - David G. Chapple
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
| | - Richard Grenyer
- School of Geography and the Environment, University of Oxford, Oxford, United Kingdom
| | - Tal Raz
- School of Zoology and Steinhardt Museum of Natural History, Tel Aviv University, Tel Aviv, Israel
| | | | - Reid Tingley
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
| | - Monika Böhm
- Institute of Zoology, Zoological Society of London, London, United Kingdom
- Global Center for Species Survival, Indianapolis Zoological Society, Indianapolis, Indiana, United States of America
| | - Shai Meiri
- School of Zoology and Steinhardt Museum of Natural History, Tel Aviv University, Tel Aviv, Israel
| | - Uri Roll
- Mitrani Department of Desert Ecology, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
- * E-mail:
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16
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Silva SV, Andermann T, Zizka A, Kozlowski G, Silvestro D. Global Estimation and Mapping of the Conservation Status of Tree Species Using Artificial Intelligence. FRONTIERS IN PLANT SCIENCE 2022; 13:839792. [PMID: 35574125 PMCID: PMC9100559 DOI: 10.3389/fpls.2022.839792] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 03/07/2022] [Indexed: 05/03/2023]
Abstract
Trees are fundamental for Earth's biodiversity as primary producers and ecosystem engineers and are responsible for many of nature's contributions to people. Yet, many tree species at present are threatened with extinction by human activities. Accurate identification of threatened tree species is necessary to quantify the current biodiversity crisis and to prioritize conservation efforts. However, the most comprehensive dataset of tree species extinction risk-the Red List of the International Union for the Conservation of Nature (IUCN RL)-lacks assessments for a substantial number of known tree species. The RL is based on a time-consuming expert-based assessment process, which hampers the inclusion of less-known species and the continued updating of extinction risk assessments. In this study, we used a computational pipeline to approximate RL extinction risk assessments for more than 21,000 tree species (leading to an overall assessment of 89% of all known tree species) using a supervised learning approach trained based on available IUCN RL assessments. We harvested the occurrence data for tree species worldwide from online databases, which we used with other publicly available data to design features characterizing the species' geographic range, biome and climatic affinities, and exposure to human footprint. We trained deep neural network models to predict their conservation status, based on these features. We estimated 43% of the assessed tree species to be threatened with extinction and found taxonomic and geographic heterogeneities in the distribution of threatened species. The results are consistent with the recent estimates by the Global Tree Assessment initiative, indicating that our approach provides robust and time-efficient approximations of species' IUCN RL extinction risk assessments.
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Affiliation(s)
- Sandro Valerio Silva
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Interfaculty Bioinformatics Unit, University of Bern, Bern, Switzerland
| | - Tobias Andermann
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Global Gothenburg Biodiversity Centre, Department of Biological and Environmental Sciences, Sweden, University of Gothenburg, Gothenburg, Sweden
| | - Alexander Zizka
- Department of Biology, Philipps-University Marburg, Marburg, Germany
| | - Gregor Kozlowski
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | - Daniele Silvestro
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Global Gothenburg Biodiversity Centre, Department of Biological and Environmental Sciences, Sweden, University of Gothenburg, Gothenburg, Sweden
- Swiss Institute of Bioinformatics, Fribourg, Switzerland
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17
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Analysis of biodiversity data suggests that mammal species are hidden in predictable places. Proc Natl Acad Sci U S A 2022; 119:e2103400119. [PMID: 35344422 PMCID: PMC9168487 DOI: 10.1073/pnas.2103400119] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Only an estimated 1 to 10% of Earth’s species have been formally described. This discrepancy between the number of species with a formal taxonomic description and actual number of species (i.e., the Linnean shortfall) hampers research across the biological sciences. To explore whether the Linnean shortfall results from poor taxonomic practice or not enough taxonomic effort, we applied machine-learning techniques to build a predictive model to identify named species that are likely to contain hidden diversity. Results indicate that small-bodied species with large, climatically variable ranges are most likely to contain hidden species. These attributes generally match those identified in the taxonomic literature, indicating that the Linnean shortfall is caused by societal underinvestment in taxonomy rather than poor taxonomic practice. Research in the biological sciences is hampered by the Linnean shortfall, which describes the number of hidden species that are suspected of existing without formal species description. Using machine learning and species delimitation methods, we built a predictive model that incorporates some 5.0 × 105 data points for 117 species traits, 3.3 × 106 occurrence records, and 9.1 × 105 gene sequences from 4,310 recognized species of mammals. Delimitation results suggest that there are hundreds of undescribed species in class Mammalia. Predictive modeling indicates that most of these hidden species will be found in small-bodied taxa with large ranges characterized by high variability in temperature and precipitation. As demonstrated by a quantitative analysis of the literature, such taxa have long been the focus of taxonomic research. This analysis supports taxonomic hypotheses regarding where undescribed diversity is likely to be found and highlights the need for investment in taxonomic research to overcome the Linnean shortfall.
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18
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Pironon S, Gómez D, Font X, García MB. Living at the limit in the Pyrenees: Peripheral and endemic plants are rare but underrepresented in protection lists. DIVERS DISTRIB 2022. [DOI: 10.1111/ddi.13487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
| | - Daniel Gómez
- Pyrenean Institute of Ecology (IPE‐CSIC) Jaca Spain
| | - Xavier Font
- Plant Biodiversity Resource Centre University of Barcelona Barcelona Spain
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19
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Levin MO, Meek JB, Boom B, Kross SM, Eskew EA. Using publicly available data to conduct rapid assessments of extinction risk. CONSERVATION SCIENCE AND PRACTICE 2022. [DOI: 10.1111/csp2.12628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Michael O. Levin
- Ecology, Evolution, and Environmental Biology Columbia University New York New York USA
| | - Jared B. Meek
- Ecology, Evolution, and Environmental Biology Columbia University New York New York USA
| | - Brian Boom
- New York Botanical Garden Bronx New York USA
| | - Sara M. Kross
- Ecology, Evolution, and Environmental Biology Columbia University New York New York USA
| | - Evan A. Eskew
- Department of Biology Pacific Lutheran University Tacoma Washington USA
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20
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OUP accepted manuscript. J Mammal 2022. [DOI: 10.1093/jmammal/gyac005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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21
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Bridging the research-implementation gap in IUCN Red List assessments. Trends Ecol Evol 2022; 37:359-370. [DOI: 10.1016/j.tree.2021.12.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 12/01/2021] [Accepted: 12/07/2021] [Indexed: 12/11/2022]
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22
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Zizka A, Andermann T, Silvestro D. IUCNN
– Deep learning approaches to approximate species' extinction risk. DIVERS DISTRIB 2021. [DOI: 10.1111/ddi.13450] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Affiliation(s)
- Alexander Zizka
- German Center for Integrative Biodiversity Research Halle‐Jena‐Leipzig (iDiv)University of Leipzig Leipzig Germany
- Department of Biology Philipps‐University Marburg Marburg Germany
| | - Tobias Andermann
- Department of Biological and Environmental Sciences University of Gothenburg Göteborg Sweden
- Gothenburg Global Biodiversity Centre Göteborg Sweden
| | - Daniele Silvestro
- Department of Biology University of Fribourg Fribourg Switzerland
- Swiss Institute of Bioinformatics Lausanne Switzerland
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23
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Daru BH, Davies TJ, Willis CG, Meineke EK, Ronk A, Zobel M, Pärtel M, Antonelli A, Davis CC. Widespread homogenization of plant communities in the Anthropocene. Nat Commun 2021; 12:6983. [PMID: 34873159 PMCID: PMC8648934 DOI: 10.1038/s41467-021-27186-8] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 11/08/2021] [Indexed: 11/24/2022] Open
Abstract
Native biodiversity decline and non-native species spread are major features of the Anthropocene. Both processes can drive biotic homogenization by reducing trait and phylogenetic differences in species assemblages between regions, thus diminishing the regional distinctiveness of biotas and likely have negative impacts on key ecosystem functions. However, a global assessment of this phenomenon is lacking. Here, using a dataset of >200,000 plant species, we demonstrate widespread and temporal decreases in species and phylogenetic turnover across grain sizes and spatial extents. The extent of homogenization within major biomes is pronounced and is overwhelmingly explained by non-native species naturalizations. Asia and North America are major sources of non-native species; however, the species they export tend to be phylogenetically close to recipient floras. Australia, the Pacific and Europe, in contrast, contribute fewer species to the global pool of non-natives, but represent a disproportionate amount of phylogenetic diversity. The timeline of most naturalisations coincides with widespread human migration within the last ~500 years, and demonstrates the profound influence humans exert on regional biotas beyond changes in species richness. Human-driven movements and extinctions of species have made plant communities across biomes more homogenous. Here the authors quantify plant vascular species and phylogenetic homogenization across the globe, finding that non-native species naturalisations have been a major driver.
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Affiliation(s)
- Barnabas H Daru
- Department of Life Sciences, Texas A&M University-Corpus Christi, Corpus Christi, TX, 78412, USA. .,Department of Organismic and Evolutionary Biology, Harvard University Herbaria, Cambridge, MA, 02138, USA.
| | - T Jonathan Davies
- Departments of Botany, and Forest & Conservation Sciences, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
| | - Charles G Willis
- Department of Biology Teaching and Learning, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Emily K Meineke
- Department of Entomology and Nematology, University of California, Davis, CA, 95616, USA
| | - Argo Ronk
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Martin Zobel
- Institute of Ecology and Earth Sciences, University of Tartu, Lai 40, EE-51005, Tartu, Estonia
| | - Meelis Pärtel
- Institute of Ecology and Earth Sciences, University of Tartu, Lai 40, EE-51005, Tartu, Estonia
| | - Alexandre Antonelli
- Department of Organismic and Evolutionary Biology, Harvard University Herbaria, Cambridge, MA, 02138, USA.,University of Gothenburg and Gothenburg Global Biodiversity Centre, Department of Biological and Environmental Sciences, Carl Skottsbergs gata 22B, SE 405 30, Gothenburg, Sweden.,Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK.,Royal Botanic Gardens, Kew, Richmond, Surrey, TW9 3AE, UK
| | - Charles C Davis
- Department of Organismic and Evolutionary Biology, Harvard University Herbaria, Cambridge, MA, 02138, USA.
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24
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Martín‐Forés I, Guerin GR, Munroe SEM, Sparrow B. Applying conservation reserve design strategies to define ecosystem monitoring priorities. Ecol Evol 2021; 11:17060-17070. [PMID: 34938492 PMCID: PMC8668797 DOI: 10.1002/ece3.8344] [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] [Received: 08/08/2021] [Accepted: 10/28/2021] [Indexed: 11/16/2022] Open
Abstract
In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long-time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well-known approaches for conservation design, the "minimum set" and the "maximal coverage" problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot-by-plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long-term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range-rarity-richness was balanced in terms of complementarity and representativeness, whereas its richness-corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision-making.
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Affiliation(s)
- Irene Martín‐Forés
- School of Biological SciencesThe University of AdelaideAdelaideSAAustralia
- Terrestrial Ecosystem Research Network (TERN)University of AdelaideAdelaideSAAustralia
| | - Greg R. Guerin
- School of Biological SciencesThe University of AdelaideAdelaideSAAustralia
- Terrestrial Ecosystem Research Network (TERN)University of AdelaideAdelaideSAAustralia
| | - Samantha E. M. Munroe
- School of Biological SciencesThe University of AdelaideAdelaideSAAustralia
- Terrestrial Ecosystem Research Network (TERN)University of AdelaideAdelaideSAAustralia
| | - Ben Sparrow
- School of Biological SciencesThe University of AdelaideAdelaideSAAustralia
- Terrestrial Ecosystem Research Network (TERN)University of AdelaideAdelaideSAAustralia
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25
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Identifying science-policy consensus regions of high biodiversity value and institutional recognition. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2021.e01938] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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26
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Shay JE, Pennington LK, Mandussi Montiel-Molina JA, Toews DJ, Hendrickson BT, Sexton JP. Rules of Plant Species Ranges: Applications for Conservation Strategies. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.700962] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Earth is changing rapidly and so are many plant species’ ranges. Here, we synthesize eco-evolutionary patterns found in plant range studies and how knowledge of species ranges can inform our understanding of species conservation in the face of global change. We discuss whether general biogeographic “rules” are reliable and how they can be used to develop adaptive conservation strategies of native plant species across their ranges. Rules considered include (1) factors that set species range limits and promote range shifts; (2) the impact of biotic interactions on species range limits; (3) patterns of abundance and adaptive properties across species ranges; (4) patterns of gene flow and their implications for genetic rescue, and (5) the relationship between range size and conservation risk. We conclude by summarizing and evaluating potential species range rules to inform future conservation and management decisions. We also outline areas of research to better understand the adaptive capacity of plants under environmental change and the properties that govern species ranges. We advise conservationists to extend their work to specifically consider peripheral and novel populations, with a particular emphasis on small ranges. Finally, we call for a global effort to identify, synthesize, and analyze prevailing patterns or rules in ecology to help speed conservation efforts.
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Texier N, Dauby G, Bidault E, Lowry PP, Ikabanga DU, Stévart T. An efficient method for defining plant species under High Conservation Value (HCV) criterion 1 based on the IUCN Red List criteria: A case study using species endemic to Gabon. J Nat Conserv 2021. [DOI: 10.1016/j.jnc.2021.126027] [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]
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28
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Meyer H, Pebesma E. Predicting into unknown space? Estimating the area of applicability of spatial prediction models. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13650] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Hanna Meyer
- Institute of Landscape Ecology Westfälische Wilhelms‐Universität Münster Münster Germany
| | - Edzer Pebesma
- Institute for Geoinformatics Westfälische Wilhelms‐Universität Münster Münster Germany
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29
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Tallis H, Fargione J, Game E, McDonald R, Baumgarten L, Bhagabati N, Cortez R, Griscom B, Higgins J, Kennedy CM, Kiesecker J, Kroeger T, Leberer T, McGowan J, Mandle L, Masuda YJ, Morrison SA, Palmer S, Shirer R, Shyamsundar P, Wolff NH, Possingham HP. Prioritizing actions: spatial action maps for conservation. Ann N Y Acad Sci 2021; 1505:118-141. [PMID: 34176148 PMCID: PMC9290997 DOI: 10.1111/nyas.14651] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 05/24/2021] [Accepted: 05/27/2021] [Indexed: 01/22/2023]
Abstract
Spatial prioritization is a critical step in conservation planning, a process designed to ensure that limited resources are applied in ways that deliver the highest possible returns for biodiversity and human wellbeing. In practice, many spatial prioritizations fall short of their potential by focusing on places rather than actions, and by using data of snapshots of assets or threats rather than estimated impacts. We introduce spatial action mapping as an approach that overcomes these shortfalls. This approach produces a spatially explicit view of where and how much a given conservation action is likely to contribute to achieving stated conservation goals. Through seven case examples, we demonstrate simple to complex versions of how this method can be applied across local to global scales to inform decisions about a wide range of conservation actions and benefits. Spatial action mapping can support major improvements in efficient use of conservation resources and will reach its full potential as the quality of environmental, social, and economic datasets converge and conservation impact evaluations improve.
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Affiliation(s)
- Heather Tallis
- Institute on the Environment, University of Minnesota, Minneapolis, Minnesota.,School of Public Health, University of California, Berkeley, Santa Cruz, California
| | - Joe Fargione
- North America Program, the Nature Conservancy, Minneapolis, Minnesota
| | - Edward Game
- Global Science, the Nature Conservancy, Arlington, Virginia
| | - Rob McDonald
- Center for Sustainability Science, the Nature Conservancy, Arlington, Virginia
| | | | | | - Rane Cortez
- Indigenous Peoples and Local Communities, the Nature Conservancy, Minneapolis, Minnesota
| | - Bronson Griscom
- Center for Natural Climate Solutions, Conservation International, Arlington, Virginia
| | - Jonathan Higgins
- Global Freshwater Team, the Nature Conservancy, Chicago, Illinois
| | - Christina M Kennedy
- Protect Oceans, Lands and Waters Program, the Nature Conservancy, Fort Collins, Colorado
| | - Joe Kiesecker
- Protect Oceans, Lands and Waters Program, the Nature Conservancy, Fort Collins, Colorado
| | - Timm Kroeger
- Global Science, the Nature Conservancy, Arlington, Virginia
| | - Trina Leberer
- Pacific Division, the Nature Conservancy, Yona, Guam
| | - Jennifer McGowan
- Global Science, the Nature Conservancy, Arlington, Virginia.,Center for Biodiversity and Global Change, Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut
| | - Lisa Mandle
- Natural Capital Project, Woods Institute for the Environment and Department of Biology, Stanford University, Stanford, California
| | - Yuta J Masuda
- Global Science, the Nature Conservancy, Arlington, Virginia
| | - Scott A Morrison
- California Program, the Nature Conservancy, San Francisco, California
| | - Sally Palmer
- Tennessee Program, the Nature Conservancy, Nashville, Tennessee
| | - Rebecca Shirer
- New York Program, the Nature Conservancy, New York City, New York
| | | | | | - Hugh P Possingham
- Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, Queensland, Australia
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30
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Cámara-Leret R, Bascompte J. Language extinction triggers the loss of unique medicinal knowledge. Proc Natl Acad Sci U S A 2021; 118:e2103683118. [PMID: 34103398 PMCID: PMC8214696 DOI: 10.1073/pnas.2103683118] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Over 30% of the 7,400 languages in the world will no longer be spoken by the end of the century. So far, however, our understanding of whether language extinction may result in the loss of linguistically unique knowledge remains limited. Here, we ask to what degree indigenous knowledge of medicinal plants is associated with individual languages and quantify how much indigenous knowledge may vanish as languages and plants go extinct. Focusing on three regions that have a high biocultural diversity, we show that over 75% of all 12,495 medicinal plant services are linguistically unique-i.e., only known to one language. Whereas most plant species associated with linguistically unique knowledge are not threatened, most languages that report linguistically unique knowledge are. Our finding of high uniqueness in indigenous knowledge and strong coupling with threatened languages suggests that language loss will be even more critical to the extinction of medicinal knowledge than biodiversity loss.
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Affiliation(s)
- Rodrigo Cámara-Leret
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, CH-8057 Zurich, Switzerland
| | - Jordi Bascompte
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, CH-8057 Zurich, Switzerland
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31
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Zizka A, Silvestro D, Vitt P, Knight TM. Automated conservation assessment of the orchid family with deep learning. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2021; 35:897-908. [PMID: 32841461 DOI: 10.1111/cobi.13616] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 05/07/2023]
Abstract
International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.
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Affiliation(s)
- Alexander Zizka
- German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig, 04103, Germany
- Naturalis Biodiversity Centre, P.O. Box 9517, Leiden, 2300RA, the Netherlands
| | - Daniele Silvestro
- Department of Biology, University of Fribourg, 1700 Fribourg, Ch. de Musee 10, Switzerland
- Gothenburg Global Biodiversity Center, University of Gothenburg, Box 461, Gothenburg, 405 30, Sweden
| | - Pati Vitt
- German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig, 04103, Germany
- Plant Biology and Conservation, Northwestern University, Evanston, IL, 60208, U.S.A
| | - Tiffany M Knight
- German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig, 04103, Germany
- Institute of Biology, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108, Halle (Saale), Germany
- Department of Community Ecology, Helmholtz Centre for Environmental Research - UFZ, Theodor-Lieser-Strasse 4, 06120, Halle (Saale), Germany
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32
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Song H, Ordonez A, Svenning JC, Qian H, Yin X, Mao L, Deng T, Zhang J. Regional disparity in extinction risk: Comparison of disjunct plant genera between eastern Asia and eastern North America. GLOBAL CHANGE BIOLOGY 2021; 27:1904-1914. [PMID: 33474767 DOI: 10.1111/gcb.15525] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 11/13/2020] [Accepted: 01/08/2021] [Indexed: 06/12/2023]
Abstract
Climate and land cover changes are increasing threats to biodiversity globally. However, potentially varying biotic sensitivity is a major source of uncertainty for translating environmental changes to extinction risks. To reduce this uncertainty, we assessed how extinction risks will be affected by future human-driven environmental changes, focusing on 554 species from 52 disjunct plant genera between eastern Asia (EAS) and eastern North America (ENA) to control for differences in environmental sensitivity at the genus level. Species distribution models were used to estimate and compare the vulnerability of species in disjunct genera between the two regions under two climate and land cover change scenarios (RCP2.6 and RCP8.5) in the 2070s, allowing to assess the effects of differences in climate and land cover pressures. Compared with ENA, stronger pressures from climate and land cover changes along with smaller range sizes in EAS translate into a larger number and proportion of species in disjunct genera becoming threatened by the 2070s. These regional differences are more pronounced under a best-case climate scenario (RCP2.6), illustrating that strong climate change (RCP8.5) may override any regional buffer capacities. The main variables determining extinction risks differed between the two continental regions, with annual temperature range and cropland expansion being important in EAS, and annual precipitation being important in ENA. These results suggest that disparities in regional exposure to anthropogenic environmental changes may cause congeneric species with relatively similar sensitivity to have different future risks of extinction. Moreover, the findings highlight the context-specific nature of anthropogenic effects on biodiversity and the importance of making region-specific policies for conservation and restoration in response to the intensifying global changes.
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Affiliation(s)
- Houjuan Song
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus C, Denmark
- Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus C, Denmark
| | - Alejandro Ordonez
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus C, Denmark
- Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus C, Denmark
| | - Jens-Christian Svenning
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus C, Denmark
- Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus C, Denmark
| | - Hong Qian
- Research and Collections Center, Illinois State Museum, Springfield, IL, USA
| | - Xue Yin
- State Key Laboratory of Biocontrol and School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Lingfeng Mao
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing, China
| | - Tao Deng
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Jian Zhang
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China
- Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus C, Denmark
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Knapp WM, Frances A, Noss R, Naczi RFC, Weakley A, Gann GD, Baldwin BG, Miller J, McIntyre P, Mishler BD, Moore G, Olmstead RG, Strong A, Kennedy K, Heidel B, Gluesenkamp D. Vascular plant extinction in the continental United States and Canada. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2021; 35:360-368. [PMID: 32860266 PMCID: PMC8151872 DOI: 10.1111/cobi.13621] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 05/11/2023]
Abstract
Extinction rates are expected to increase during the Anthropocene. Current extinction rates of plants and many animals remain unknown. We quantified extinctions among the vascular flora of the continental United States and Canada since European settlement. We compiled data on apparently extinct species by querying plant conservation databases, searching the literature, and vetting the resulting list with botanical experts. Because taxonomic opinion varies widely, we developed an index of taxonomic uncertainty (ITU). The ITU ranges from A to F, with A indicating unanimous taxonomic recognition and F indicating taxonomic recognition by only a single author. The ITU allowed us to rigorously evaluate extinction rates. Our data suggest that 51 species and 14 infraspecific taxa, representing 33 families and 49 genera of vascular plants, have become extinct in our study area since European settlement. Seven of these taxa exist in cultivation but are extinct in the wild. Most extinctions occurred in the west, but this outcome may reflect the timing of botanical exploration relative to settlement. Sixty-four percent of extinct plants were single-site endemics, and many occurred outside recognized biodiversity hotspots. Given the paucity of plant surveys in many areas, particularly prior to European settlement, the actual extinction rate of vascular plants is undoubtedly much higher than indicated here.
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Affiliation(s)
- Wesley M. Knapp
- North Carolina Natural Heritage ProgramAshevilleNC28805U.S.A.
| | - Anne Frances
- NatureServe2550 South Clark Street, Suite 930ArlingtonVA22202‐3926U.S.A.
| | - Reed Noss
- Florida Institute for Conservation Science112 Half Moon TrailMelroseFL32666U.S.A.
| | - Robert F. C. Naczi
- Institute of Systematic Botany, New York Botanical Garden2900 Southern Blvd.BronxNY10458‐5126U.S.A.
| | - Alan Weakley
- Biology Department, North Carolina Botanical GardenUniversity of North Carolina at Chapel HillCampus Box 3280Chapel HillNC27599‐3280U.S.A.
| | - George D. Gann
- The Institute for Regional Conservation100 E. Linton Blvd. #302BDelray BeachFL33483U.S.A.
| | - Bruce G. Baldwin
- Jepson Herbarium & Department of Integrative BiologyUniversity of California1001 Valley Life Sciences Bldg. #2465BerkeleyCA94720‐2465U.S.A.
| | - James Miller
- Missouri Botanical Garden4344 Shaw Blvd.St. LouisMO63110U.S.A.
| | - Patrick McIntyre
- NatureServe2550 South Clark Street, Suite 930ArlingtonVA22202‐3926U.S.A.
| | - Brent D. Mishler
- University and Jepson Herbaria & Department of Integrative BiologyUniversity of California1001 Valley Life Sciences Bldg. #2465BerkeleyCA94720‐2465U.S.A.
| | - Gerry Moore
- National Plant Data TeamUnited States Department of Agriculture2901 East Gate City Blvd., Suite 2100GreensboroNC27041U.S.A.
| | - Richard G. Olmstead
- Department of Biology and Burke MuseumUniversity of WashingtonSeattleWA98195U.S.A.
| | - Anna Strong
- Texas Parks and Wildlife Department4200 Smith School RoadAustinTX78744U.S.A.
| | - Kathryn Kennedy
- United States Forest Service333 Broadway Blvd. SEAlbuquerqueNM87102U.S.A.
| | - Bonnie Heidel
- Wyoming Natural Diversity DatabaseUniversity of Wyoming1000 E. University AvenueLaramieWY82071U.S.A.
| | - Daniel Gluesenkamp
- California Native Plant Society2707 K Street, Suite 1SacramentoCA95816U.S.A.
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Kraus D, Murphy S, Armitage D. Ten bridges on the road to recovering Canada’s endangered species. Facets (Ott) 2021. [DOI: 10.1139/facets-2020-0084] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Wildlife is declining around the world. Many developed nations have enacted legislation on endangered species protection and provide funding for wildlife recovery. Protecting endangered species is also supported by the public and judiciary. Yet, despite what appear as enabling conditions, wild species continue to decline. Our paper explores pathways to endangered species recovery by analyzing the barriers that have been identified in Canada, the United States, and Australia. We summarize these findings based on Canada’s Species at Risk Conservation Cycle (assessment, protection, recovery planning, implementation, and monitoring and evaluation) and then identify 10 “bridges” that could help overcome these barriers and bend our current trajectory of wildlife loss to recovery. These bridges include ecosystem approaches to recovery, building capacity for community co-governance, linking wildlife recovery to ecosystem services, and improving our storytelling about the loss and recovery of wildlife. The focus of our conclusions is the Canadian setting, but our findings can be applied in other national and subnational settings to reverse the decline of wildlife and halt extinction.
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Affiliation(s)
- Daniel Kraus
- Faculty of Environment, School of Environment, Resources and Sustainability, University of Waterloo, Environment 2, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
- Nature Conservancy of Canada, 245 Eglinton Avenue East, Suite 410, Toronto, ON M4P 3J1, Canada
| | - Stephen Murphy
- Faculty of Environment, School of Environment, Resources and Sustainability, University of Waterloo, Environment 2, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
| | - Derek Armitage
- Faculty of Environment, School of Environment, Resources and Sustainability, University of Waterloo, Environment 2, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
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Tagliacollo VA, Dagosta FCP, Pinna MD, Reis RE, Albert JS. Assessing extinction risk from geographic distribution data in Neotropical freshwater fishes. NEOTROPICAL ICHTHYOLOGY 2021. [DOI: 10.1590/1982-0224-2021-0079] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Abstract The IUCN Red List (RL) provides high-quality conservation assessments for individual species, yet the rate and scale of environmental deterioration globally challenges the conservation community to develop expedited methods for risk assessment. Here we compare threat assessments for 3,001 species of Neotropical freshwater fishes (NFF) in the IUCN–RL using readily accessible data types as proxies for extinction risk: geographic range, elevation, and species publication date. Furthermore, using geographic and taxonomic data alone, we generated preliminary conservation assessments for 2,334 NFF species currently awaiting IUCN assessment, identifying an additional 671 NFF species as potentially threatened. This number of potentially threatened species represents an increase of 59% over the number of species currently assigned to threat categories by the IUCN–RL. These results substantially expand the number of threatened NFF species from 422 currently on the IUCN RL to 1,093 species as threatened or potentially threatened, representing about 18% of all NFF species. Extinction risk is greater in species with smaller geographic ranges, which inhabit upland rivers, and which were described more recently. We propose the Central and Southern Andes, and Eastern Guiana Shield as priorities in the upcoming IUCN RL assessment of NFF species conservation risk.
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Affiliation(s)
| | | | - Mário de Pinna
- 1 Museu de Zoologia da Universidade de São Paulo, Brazil
| | - Roberto E. Reis
- Pontifícia Universidade Católica do Rio Grande do Sul, Brazil
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Gowthami R, Sharma N, Pandey R, Agrawal A. Status and consolidated list of threatened medicinal plants of India. GENETIC RESOURCES AND CROP EVOLUTION 2021; 68:2235-2263. [PMID: 34054223 PMCID: PMC8148398 DOI: 10.1007/s10722-021-01199-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 04/29/2021] [Indexed: 05/13/2023]
Abstract
A wide array of medicinal plants in India, primarily used by locals for health care, have found wide acceptance and adoption globally (either directly or processed) due to distinct advantages of good results, low or no side-effects and ease of access to general public. Indigenous and traditional systems of medicine in practice since historical times have shown potential (direct or indirect as immune-boosters) against many dreaded ailments including the recent global pandemic of COVID-19. With prediction of sixth mass extinction, there is worldwide concern as majority of these plants, collected from natural stands, are also facing threat of extinction. Since 1990s concerted efforts have been directed towards assessment of threat status, the basic requirement for prioritizing conservation activity to various species of plants and animals. In literature there is staggered information regarding list of threatened plants, including medicinal plants of India, compiled at either state level or national or international level. Analysis of these publications led to collation of a consolidated list of 84 species and the same is presented here. A brief account of conservation efforts in India at national level and supportive policy framework is also included. This compilation is aimed to serve as a comprehensive reference especially for beginners, researchers, conservationists, foresters, pharmaceutical professionals as well as policy makers.
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Affiliation(s)
- R. Gowthami
- Tissue Culture and Cryopreservation Unit, ICAR-National Bureau of Plant Genetic Resources (NBPGR), Pusa Campus, New Delhi, 110012 India
| | - Neelam Sharma
- Tissue Culture and Cryopreservation Unit, ICAR-National Bureau of Plant Genetic Resources (NBPGR), Pusa Campus, New Delhi, 110012 India
| | - Ruchira Pandey
- Tissue Culture and Cryopreservation Unit, ICAR-National Bureau of Plant Genetic Resources (NBPGR), Pusa Campus, New Delhi, 110012 India
| | - Anuradha Agrawal
- Tissue Culture and Cryopreservation Unit, ICAR-National Bureau of Plant Genetic Resources (NBPGR), Pusa Campus, New Delhi, 110012 India
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37
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Velazco SJE, Svenning J, Ribeiro BR, Laureto LMO. On opportunities and threats to conserve the phylogenetic diversity of Neotropical palms. DIVERS DISTRIB 2020. [DOI: 10.1111/ddi.13215] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Affiliation(s)
- Santiago José Elías Velazco
- Instituto de Biología Subtropical Universidad Nacional de Misiones‐CONICET Puerto Iguazú Misiones N3370BFAArgentina
| | - Jean‐Christian Svenning
- Section of Ecoinformatics and Biodiversity, Department of Bioscience Aarhus University AarhusDK‐8000Denmark
- Center for Biodiversity Dynamics in a Changing World (BIOCHANGE) Department of Bioscience, Aarhus University AarhusDK‐8000Denmark
| | - Bruno R. Ribeiro
- Programa de Pós‐Graduaçao Ecología e Evolução Instituto de Ciências Biológicas V, Universidade Federal de Goiás Goiânia Goiás 74.690‐900Brazil
| | - Livia Maira Orlandi Laureto
- Theoretical, Metacommunity and Landscape Ecology Laboratory Instituto de Ciências Biológicas V, Universidade Federal de Goiás Goiânia Goiás 74.690‐900Brazil
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Pañitrur‐De la Fuente C, Ibáñez ST, León MF, Martínez‐Tilleria K, Sandoval A. Conservation of native plants in the seed base Bank of Chile. CONSERVATION SCIENCE AND PRACTICE 2020. [DOI: 10.1111/csp2.292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
| | - Sergio T. Ibáñez
- Instituto de Investigaciones Agropecuarias (INIA) Centro Regional de Investigación Intihuasi Vicuña Chile
| | - Mario F. León
- Instituto de Investigaciones Agropecuarias (INIA) Centro Regional de Investigación Intihuasi Vicuña Chile
| | | | - Ana Sandoval
- Instituto de Investigaciones Agropecuarias (INIA) Centro Regional de Investigación Intihuasi Vicuña Chile
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Zizka A, Antunes Carvalho F, Calvente A, Rocio Baez-Lizarazo M, Cabral A, Coelho JFR, Colli-Silva M, Fantinati MR, Fernandes MF, Ferreira-Araújo T, Gondim Lambert Moreira F, Santos NMC, Santos TAB, Dos Santos-Costa RC, Serrano FC, Alves da Silva AP, de Souza Soares A, Cavalcante de Souza PG, Calisto Tomaz E, Vale VF, Vieira TL, Antonelli A. No one-size-fits-all solution to clean GBIF. PeerJ 2020; 8:e9916. [PMID: 33062422 PMCID: PMC7528811 DOI: 10.7717/peerj.9916] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 08/20/2020] [Indexed: 12/05/2022] Open
Abstract
Species occurrence records provide the basis for many biodiversity studies. They derive from georeferenced specimens deposited in natural history collections and visual observations, such as those obtained through various mobile applications. Given the rapid increase in availability of such data, the control of quality and accuracy constitutes a particular concern. Automatic filtering is a scalable and reproducible means to identify potentially problematic records and tailor datasets from public databases such as the Global Biodiversity Information Facility (GBIF; http://www.gbif.org), for biodiversity analyses. However, it is unclear how much data may be lost by filtering, whether the same filters should be applied across all taxonomic groups, and what the effect of filtering is on common downstream analyses. Here, we evaluate the effect of 13 recently proposed filters on the inference of species richness patterns and automated conservation assessments for 18 Neotropical taxa, including terrestrial and marine animals, fungi, and plants downloaded from GBIF. We find that a total of 44.3% of the records are potentially problematic, with large variation across taxonomic groups (25–90%). A small fraction of records was identified as erroneous in the strict sense (4.2%), and a much larger proportion as unfit for most downstream analyses (41.7%). Filters of duplicated information, collection year, and basis of record, as well as coordinates in urban areas, or for terrestrial taxa in the sea or marine taxa on land, have the greatest effect. Automated filtering can help in identifying problematic records, but requires customization of which tests and thresholds should be applied to the taxonomic group and geographic area under focus. Our results stress the importance of thorough recording and exploration of the meta-data associated with species records for biodiversity research.
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Affiliation(s)
- Alexander Zizka
- sDiv, German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig (iDiv), Leipzig, Germany.,Naturalis Biodiversity Center, Leiden, The Netherlands
| | - Fernanda Antunes Carvalho
- Departamento de Genética, Ecologia e Evolução, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Alice Calvente
- Departamento de Botânica e Zoologia, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | | | - Andressa Cabral
- Departamento de Botânica, Universidade de São Paulo, São Paulo, Brazil
| | | | | | - Mariana Ramos Fantinati
- Departamento de Botânica e Zoologia, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Moabe F Fernandes
- Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, Feira de Santana, Brazil
| | - Thais Ferreira-Araújo
- Departamento de Botânica e Zoologia, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | | | | | | | | | - Filipe C Serrano
- Departamento de Ecologia, Universidade de São Paulo, São Paulo, Brazil
| | | | - Arthur de Souza Soares
- Departamento de Botânica e Zoologia, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | | | - Eduardo Calisto Tomaz
- Departamento de Botânica e Zoologia, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Valéria Fonseca Vale
- Departamento de Botânica e Zoologia, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Tiago Luiz Vieira
- Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, Feira de Santana, Brazil
| | - Alexandre Antonelli
- Gothenburg Global Biodiversity Centre, University of Gothenburg, Gothenburg, Sweden.,Department for Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden.,Royal Botanic Gardens Kew, Richmond, United Kingdom
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40
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Nic Lughadha E, Bachman SP, Leão TCC, Forest F, Halley JM, Moat J, Acedo C, Bacon KL, Brewer RFA, Gâteblé G, Gonçalves SC, Govaerts R, Hollingsworth PM, Krisai‐Greilhuber I, Lirio EJ, Moore PGP, Negrão R, Onana JM, Rajaovelona LR, Razanajatovo H, Reich PB, Richards SL, Rivers MC, Cooper A, Iganci J, Lewis GP, Smidt EC, Antonelli A, Mueller GM, Walker BE. Extinction risk and threats to plants and fungi. PLANTS, PEOPLE, PLANET 2020; 2:389-408. [PMID: 0 DOI: 10.1002/ppp3.10146] [Citation(s) in RCA: 94] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 06/09/2020] [Indexed: 05/29/2023]
Affiliation(s)
| | - Steven P. Bachman
- Conservation Science Department Royal Botanic Gardens, Kew Richmond UK
| | | | - Félix Forest
- Analytical Methods Royal Botanic Gardens, Kew Richmond UK
| | - John M. Halley
- Laboratory of Ecology Department of Biological Applications & Technology University of Ioannina Ioannina Greece
| | - Justin Moat
- Bioinformatics and Spatial Analysis Department Royal Botanic Gardens, Kew Richmond UK
| | - Carmen Acedo
- Department of Biodiversity and Environment Management Faculty of Biological and Environmental Sciences Campus of Vegazana University of León León Spain
| | - Karen L. Bacon
- Botany & Plant Sciences School of Natural Sciences National University of Ireland Galway Ireland
| | - Ryan F. A. Brewer
- Conservation Science Department Royal Botanic Gardens, Kew Richmond UK
| | - Gildas Gâteblé
- Equipe ARBOREAL Institut Agronomique néo‐Calédonien Mont‐Dore New Caledonia
| | - Susana C. Gonçalves
- Centre for Functional Ecology Department of Life Sciences University of Coimbra Coimbra Portugal
| | - Rafaël Govaerts
- Bioinformatics and Spatial Analysis Department Royal Botanic Gardens, Kew Richmond UK
| | | | - Irmgard Krisai‐Greilhuber
- Mycology Research Group Division of Systematic and Evolutionary Biology Department of Botany and Biodiversity Research University of Vienna Vienna Austria
| | - Elton J. Lirio
- Departamento de Botânica Instituto de Biociências Universidade de São Paulo São Paulo Brazil
| | | | - Raquel Negrão
- Conservation Science Department Royal Botanic Gardens, Kew Richmond UK
| | - Jean Michel Onana
- Systematics, Biodiversity and Conservation of Plants Faculty of Science University of Yaoundé I & National Herbarium of Cameroon Yaoundé Cameroon
| | - Landy R. Rajaovelona
- Conservation Science Department Royal Botanic Gardens, Kew Richmond UK
- Kew Madagascar Conservation Centre Antananarivo Madagascar
| | - Henintsoa Razanajatovo
- Conservation Science Department Royal Botanic Gardens, Kew Richmond UK
- Kew Madagascar Conservation Centre Antananarivo Madagascar
| | - Peter B. Reich
- Department of Forest Resources University of Minnesota St. Paul MN USA
- Hawkesbury Institute for the Environment Western Sydney University Penrith NSW Australia
| | | | | | - Amanda Cooper
- Bioinformatics and Spatial Analysis Department Royal Botanic Gardens, Kew Richmond UK
- Department of Biological Sciences Royal HollowayUniversity of London Egham UK
| | - João Iganci
- Instituto de Biologia Departamento de Botânica Universidade Federal de Pelotas Pelotas Brazil
- Instituto de Biociências Programa de Pós‐Graduação em Botânica Universidade Federal do Rio Grande do Sul Porto Alegre Brazil
| | - Gwilym P. Lewis
- Comparative Plant and Fungal Biology Royal Botanic Gardens, Kew Richmond UK
| | - Eric C. Smidt
- Departamento de Botânica Universidade Federal do Paraná Curitiba Brazil
| | - Alexandre Antonelli
- Royal Botanic Gardens, Kew Richmond UK
- Gothenburg Global Biodiversity Centre Department of Biological and Environmental Sciences University of Gothenburg Gothenburg Sweden
| | - Gregory M. Mueller
- Negaunee Institute for Plant Conservation Science and Action Chicago Botanic Garden Chicago IL USA
| | - Barnaby E. Walker
- Conservation Science Department Royal Botanic Gardens, Kew Richmond UK
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41
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Diversity of Tree Species in Gap Regeneration under Tropical Moist Semi-Deciduous Forest: An Example from Bia Tano Forest Reserve. DIVERSITY 2020. [DOI: 10.3390/d12080301] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
In a quest to improve the diversity and conservation of native tree species in tropical African forests, gap regeneration remains all-important nature-promoting silviculture practice and ecosystem-based strategy for attaining these ecological goals. Nine gaps of varying sizes (286–2005 m2) were randomly selected: three each from undisturbed, slightly disturbed and disturbed areas within Bia Tano Forest Reserve of Ghana. Within individual gaps, four transects (North–South–East–West directions) followed by 10 subsampling regions of 1 m2 at 2 m apart were established along each transect. Data showed 63 tree species from 21 families in the study. Although, all estimated diversity indices showed significant biodiversity improvements in all gaps at p < 0.05 level. Yet, there were no significant variations amongst gaps. Additionally, tree species differed between gaps at the undisturbed and the two disturbance-graded areas while no differences were presented between disturbance-graded areas. Balanced conservation between Green Star and Reddish Star species and imbalanced conservation between Least Concern, Near Threatened and Vulnerable species in the International Union for Conservation of Nature (IUCN) Red List were found, showing the reserve’s long-term prospects for economic and ecological benefits of forest management. Thus, there is a need for higher priority for intensive management to regulate various anthropogenic disturbances so as to protect the biological legacies of the reserve.
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42
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Li B, Yaegashi S, Carvajal TM, Gamboa M, Chiu M, Ren Z, Watanabe K. Machine-learning-based detection of adaptive divergence of the stream mayfly Ephemera strigata populations. Ecol Evol 2020; 10:6677-6687. [PMID: 32724541 PMCID: PMC7381564 DOI: 10.1002/ece3.6398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 04/21/2020] [Accepted: 04/30/2020] [Indexed: 11/07/2022] Open
Abstract
Adaptive divergence is a key mechanism shaping the genetic variation of natural populations. A central question linking ecology with evolutionary biology is how spatial environmental heterogeneity can lead to adaptive divergence among local populations within a species. In this study, using a genome scan approach to detect candidate loci under selection, we examined adaptive divergence of the stream mayfly Ephemera strigata in the Natori River Basin in northeastern Japan. We applied a new machine-learning method (i.e., random forest) besides traditional distance-based redundancy analysis (dbRDA) to examine relationships between environmental factors and adaptive divergence at non-neutral loci. Spatial autocorrelation analysis based on neutral loci was employed to examine the dispersal ability of this species. We conclude the following: (a) E. strigata show altitudinal adaptive divergence among the populations in the Natori River Basin; (b) random forest showed higher resolution for detecting adaptive divergence than traditional statistical analysis; and (c) separating all markers into neutral and non-neutral loci could provide full insight into parameters such as genetic diversity, local adaptation, and dispersal ability.
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Affiliation(s)
- Bin Li
- Insititute of Environmental and EcologyShandong Normal UniversityJinanChina
- Department of Civil and Environmental EngineeringEhime UniversityMatsuyamaJapan
| | - Sakiko Yaegashi
- Department of Civil and Environmental EngineeringEhime UniversityMatsuyamaJapan
- Department of Civil and Environmental EngineeringUniversity of YamanashiYamanashiJapan
| | | | - Maribet Gamboa
- Department of Civil and Environmental EngineeringEhime UniversityMatsuyamaJapan
| | - Ming‐Chih Chiu
- Department of Civil and Environmental EngineeringEhime UniversityMatsuyamaJapan
| | - Zongming Ren
- Insititute of Environmental and EcologyShandong Normal UniversityJinanChina
| | - Kozo Watanabe
- Department of Civil and Environmental EngineeringEhime UniversityMatsuyamaJapan
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43
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Fukaya K, Kusumoto B, Shiono T, Fujinuma J, Kubota Y. Integrating multiple sources of ecological data to unveil macroscale species abundance. Nat Commun 2020; 11:1695. [PMID: 32245942 PMCID: PMC7125090 DOI: 10.1038/s41467-020-15407-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 02/27/2020] [Indexed: 12/02/2022] Open
Abstract
The pattern of species abundance, represented by the number of individuals per species within an ecological community, is one of the fundamental characteristics of biodiversity. However, despite their obvious significance in ecology and biogeography, there is still no clear understanding of these patterns at large spatial scales. Here, we develop a hierarchical modelling approach to estimate macroscale patterns of species abundance. Using this approach, estimates of absolute abundance of 1248 woody plant species at a 10-km-grid-square resolution over East Asian islands across subtropical to temperate biomes are obtained. We provide two examples of the basic and applied use of the estimated species abundance for (1) inference of macroevolutionary processes underpinning regional biodiversity patterns and (2) quantitative community-wide assessment of a national red list. These results highlight the potential of the elucidation of macroscale species abundance that has thus far been an inaccessible but critical property of biodiversity. Measurement of species abundance is fundamental in ecology, yet challenging at large spatial scales. Here, the authors show estimates of abundance of 1248 woody plant species over the East Asian islands that highlight macroevolutionary processes of biodiversity and the status of the national red listing.
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Affiliation(s)
- Keiichi Fukaya
- National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan. .,The Institute of Statistical Mathematics, 10-3 Midoricho, Tachikawa, Tokyo, 190-8562, Japan.
| | - Buntarou Kusumoto
- Faculty of Science, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japan
| | - Takayuki Shiono
- Faculty of Science, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japan
| | - Junichi Fujinuma
- Faculty of Science, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japan
| | - Yasuhiro Kubota
- Faculty of Science, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japan
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44
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BDcleaner: A workflow for cleaning taxonomic and geographic errors in occurrence data archived in biodiversity databases. Glob Ecol Conserv 2020. [DOI: 10.1016/j.gecco.2019.e00852] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
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45
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Walker BE, Leão TCC, Bachman SP, Bolam FC, Nic Lughadha E. Caution Needed When Predicting Species Threat Status for Conservation Prioritization on a Global Scale. FRONTIERS IN PLANT SCIENCE 2020; 11:520. [PMID: 32411173 PMCID: PMC7199234 DOI: 10.3389/fpls.2020.00520] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 04/06/2020] [Indexed: 05/19/2023]
Affiliation(s)
- Barnaby E. Walker
- Royal Botanic Gardens, Kew, Richmond, United Kingdom
- *Correspondence: Barnaby E. Walker
| | | | | | - Friederike C. Bolam
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
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46
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Bodie Weedop K, Mooers AØ, Tucker CM, Pearse WD. Preserving evolutionary history with improved confidence. Anim Conserv 2019. [DOI: 10.1111/acv.12556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- K. Bodie Weedop
- Department of Biology & Ecology Center Utah State University Logan UT USA
| | - A. Ø. Mooers
- Department of Biological Sciences Simon Fraser University Burnaby BC Canada
| | - C. M. Tucker
- Department of Biology University of North Carolina–Chapel Hill Chapel Hill NC USA
| | - W. D. Pearse
- Department of Biology & Ecology Center Utah State University Logan UT USA
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47
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Cobb NS, Gall LF, Zaspel JM, Dowdy NJ, McCabe LM, Kawahara AY. Assessment of North American arthropod collections: prospects and challenges for addressing biodiversity research. PeerJ 2019; 7:e8086. [PMID: 31788358 PMCID: PMC6882419 DOI: 10.7717/peerj.8086] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 10/23/2019] [Indexed: 12/21/2022] Open
Abstract
Over 300 million arthropod specimens are housed in North American natural history collections. These collections represent a "vast hidden treasure trove" of biodiversity -95% of the specimen label data have yet to be transcribed for research, and less than 2% of the specimens have been imaged. Specimen labels contain crucial information to determine species distributions over time and are essential for understanding patterns of ecology and evolution, which will help assess the growing biodiversity crisis driven by global change impacts. Specimen images offer indispensable insight and data for analyses of traits, and ecological and phylogenetic patterns of biodiversity. Here, we review North American arthropod collections using two key metrics, specimen holdings and digitization efforts, to assess the potential for collections to provide needed biodiversity data. We include data from 223 arthropod collections in North America, with an emphasis on the United States. Our specific findings are as follows: (1) The majority of North American natural history collections (88%) and specimens (89%) are located in the United States. Canada has comparable holdings to the United States relative to its estimated biodiversity. Mexico has made the furthest progress in terms of digitization, but its specimen holdings should be increased to reflect the estimated higher Mexican arthropod diversity. The proportion of North American collections that has been digitized, and the number of digital records available per species, are both much lower for arthropods when compared to chordates and plants. (2) The National Science Foundation's decade-long ADBC program (Advancing Digitization of Biological Collections) has been transformational in promoting arthropod digitization. However, even if this program became permanent, at current rates, by the year 2050 only 38% of the existing arthropod specimens would be digitized, and less than 1% would have associated digital images. (3) The number of specimens in collections has increased by approximately 1% per year over the past 30 years. We propose that this rate of increase is insufficient to provide enough data to address biodiversity research needs, and that arthropod collections should aim to triple their rate of new specimen acquisition. (4) The collections we surveyed in the United States vary broadly in a number of indicators. Collectively, there is depth and breadth, with smaller collections providing regional depth and larger collections providing greater global coverage. (5) Increased coordination across museums is needed for digitization efforts to target taxa for research and conservation goals and address long-term data needs. Two key recommendations emerge: collections should significantly increase both their specimen holdings and their digitization efforts to empower continental and global biodiversity data pipelines, and stimulate downstream research.
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Affiliation(s)
- Neil S. Cobb
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States of America
| | - Lawrence F. Gall
- Entomology Division, Yale Peabody Museum of Natural History, New Haven, CT, United States of America
| | - Jennifer M. Zaspel
- Department of Zoology, Milwaukee Public Museum, Milwaukee, WI, United States of America
- Department of Entomology, Purdue University, West Lafayette, IN, United States of America
| | - Nicolas J. Dowdy
- Department of Zoology, Milwaukee Public Museum, Milwaukee, WI, United States of America
- Department of Biology, Wake Forest University, Winston-Salem, NC, United States of America
| | - Lindsie M. McCabe
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States of America
| | - Akito Y. Kawahara
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States of America
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48
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Borrell JS, Al Issaey G, Lupton DA, Starnes T, Al Hinai A, Al Hatmi S, Senior RA, Wilkinson T, Milborrow JLH, Stokes-Rees A, Patzelt A. Islands in the desert: environmental distribution modelling of endemic flora reveals the extent of Pleistocene tropical relict vegetation in southern Arabia. ANNALS OF BOTANY 2019; 124:411-422. [PMID: 31418009 PMCID: PMC6798844 DOI: 10.1093/aob/mcz085] [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: 03/10/2019] [Accepted: 05/13/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND AIMS Southern Arabia is a global biodiversity hotspot with a high proportion of endemic desert-adapted plants. Here we examine evidence for a Pleistocene climate refugium in the southern Central Desert of Oman, and its role in driving biogeographical patterns of endemism. METHODS Distribution data for seven narrow-range endemic plants were collected systematically across 195 quadrats, together with incidental and historic records. Important environmental variables relevant to arid coastal areas, including night-time fog and cloud cover, were developed for the study area. Environmental niche models using presence/absence data were built and tuned for each species, and spatial overlap was examined. KEY RESULTS A region of the Jiddat Al Arkad reported independent high model suitability for all species. Examination of environmental data across southern Oman indicates that the Jiddat Al Arkad displays a regionally unique climate with higher intra-annual stability, due in part to the influence of the southern monsoon. Despite this, the relative importance of environmental variables was highly differentiated among species, suggesting that characteristic variables such as coastal fog are not major cross-species predictors at this scale. CONCLUSIONS The co-occurrence of a high number of endemic study species within a narrow monsoon-influenced region is indicative of a refugium with low climate change velocity. Combined with climate analysis, our findings provide strong evidence for a southern Arabian Pleistocene refugium in Oman's Central Desert. We suggest that this refugium has acted as an isolated temperate and mesic island in the desert, resulting in the evolution of these narrow-range endemic flora. Based on the composition of species, this system may represent the northernmost remnant of a continuous belt of mesic vegetation formerly ranging from Africa to Asia, with close links to the flora of East Africa. This has significant implications for future conservation of endemic plants in an arid biodiversity hotspot.
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Affiliation(s)
- James S Borrell
- Jodrell Laboratory, Royal Botanic Gardens, Kew, Richmond, Surrey, UK
| | | | | | - Thomas Starnes
- RSPB Centre for Conservation Science, Royal Society for the Protection of Birds, The Lodge, Sandy, Bedfordshire, UK
| | | | | | - Rebecca A Senior
- Department of Animal and Plant Sciences, Alfred Denny Building, University of Sheffield, Western Bank, Sheffield, UK
| | - Tim Wilkinson
- Jodrell Laboratory, Royal Botanic Gardens, Kew, Richmond, Surrey, UK
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49
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Humphreys AM, Govaerts R, Ficinski SZ, Nic Lughadha E, Vorontsova MS. Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nat Ecol Evol 2019; 3:1043-1047. [DOI: 10.1038/s41559-019-0906-2] [Citation(s) in RCA: 158] [Impact Index Per Article: 31.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 04/24/2019] [Indexed: 11/09/2022]
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50
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Sullivan J, Smith ML, Espíndola A, Ruffley M, Rankin A, Tank D, Carstens B. Integrating life history traits into predictive phylogeography. Mol Ecol 2019; 28:2062-2073. [DOI: 10.1111/mec.15029] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 01/04/2019] [Accepted: 01/16/2019] [Indexed: 11/29/2022]
Affiliation(s)
- Jack Sullivan
- Department of Biological Sciences University of Idaho Moscow Idaho
- Institute for Bioinformatics and Evolutionary Studies University of Idaho Moscow Idaho
| | - Megan L. Smith
- Department of Ecology, Evolution and Organismal Biology The Ohio State University Columbus Ohio
| | - Anahí Espíndola
- Department of Biological Sciences University of Idaho Moscow Idaho
- Department of Entomology University of Maryland College Park Maryland
| | - Megan Ruffley
- Department of Biological Sciences University of Idaho Moscow Idaho
- Institute for Bioinformatics and Evolutionary Studies University of Idaho Moscow Idaho
| | - Andrew Rankin
- Department of Biological Sciences University of Idaho Moscow Idaho
- Institute for Bioinformatics and Evolutionary Studies University of Idaho Moscow Idaho
| | - David Tank
- Department of Biological Sciences University of Idaho Moscow Idaho
- Institute for Bioinformatics and Evolutionary Studies University of Idaho Moscow Idaho
| | - Bryan Carstens
- Department of Ecology, Evolution and Organismal Biology The Ohio State University Columbus Ohio
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