No Cover Image

Book chapter 1447 views

Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project

Andy Purvis, Tim Newbold, Adriana De Palma, Sara Contu, Samantha L.L. Hill, Katia Sanchez-Ortiz, Helen R.P. Phillips, Lawrence N. Hudson, Igor Lysenko, Luca Borger Orcid Logo, Jörn P.W. Scharlemann

Next Generation Biomonitoring: Part 1, Volume: 58, Pages: 201 - 241

Swansea University Author: Luca Borger Orcid Logo

Full text not available from this repository: check for access using links below.

Check full text

DOI (Published version): 10.1016/bs.aecr.2017.12.003

Abstract

The PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) has collated ecological survey data from hundreds of published biodiversity comparisons of sites facing different land-use and related pressures, and used the resulting taxonomically and geographicall...

Full description

Published in: Next Generation Biomonitoring: Part 1
ISBN: 9780128139493
ISSN: 00652504
Published: Academic Press 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa39321
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2018-04-06T04:41:06Z
last_indexed 2023-02-15T03:48:23Z
id cronfa39321
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2023-02-14T15:25:08.5578397</datestamp><bib-version>v2</bib-version><id>39321</id><entry>2018-04-06</entry><title>Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project</title><swanseaauthors><author><sid>8416d0ffc3cccdad6e6d67a455e7c4a2</sid><ORCID>0000-0001-8763-5997</ORCID><firstname>Luca</firstname><surname>Borger</surname><name>Luca Borger</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2018-04-06</date><deptcode>SBI</deptcode><abstract>The PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) has collated ecological survey data from hundreds of published biodiversity comparisons of sites facing different land-use and related pressures, and used the resulting taxonomically and geographically broad database (abundance and occurrence data for over 50,000 species and over 30,000 sites in nearly 100 countries) to develop global biodiversity models, indicators, and projections. After outlining the science and science-policy gaps that motivated PREDICTS, this review discusses the key design decisions that helped it to achieve its objectives. In particular, we discuss basing models on a large, taxonomically, and geographically representative database, so that they may be applicable to biodiversity more broadly; space-for-time substitution, which allows estimation of pressure-state models without the need for representative time-series data; and collation of raw data rather than statistical results, greatly expanding the range of response variables that can be modelled. The heterogeneity of data in the PREDICTS database has presented a range of modelling challenges: we discuss these with a focus on our implementation of the Biodiversity Intactness Index, an indicator with considerable policy potential but which had not previously been estimated from primary biodiversity data. We then summarise the findings from analyses of how land use and related pressures affect local (&#x3B1;) diversity and spatial turnover (&#x3B2; diversity), and how these effects are mediated by ecological attributes of species. We discuss the relevance of our findings for policy, before ending with some directions of ongoing and possible future research.</abstract><type>Book chapter</type><journal>Next Generation Biomonitoring: Part 1</journal><volume>58</volume><journalNumber/><paginationStart>201</paginationStart><paginationEnd>241</paginationEnd><publisher>Academic Press</publisher><placeOfPublication/><isbnPrint>9780128139493</isbnPrint><isbnElectronic/><issnPrint>00652504</issnPrint><issnElectronic/><keywords>Biodiversity intactness index, Alpha diversity, Beta diversity, Biodiversity indicators, Biodiversity models, Hockey-stick graph, Representativeness, Meta-analysis,</keywords><publishedDay>16</publishedDay><publishedMonth>2</publishedMonth><publishedYear>2018</publishedYear><publishedDate>2018-02-16</publishedDate><doi>10.1016/bs.aecr.2017.12.003</doi><url>http://www.sciencedirect.com/science/article/pii/S0065250417300284</url><notes/><college>COLLEGE NANME</college><department>Biosciences</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SBI</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2023-02-14T15:25:08.5578397</lastEdited><Created>2018-04-06T00:06:49.2310091</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Biosciences, Geography and Physics - Biosciences</level></path><authors><author><firstname>Andy</firstname><surname>Purvis</surname><order>1</order></author><author><firstname>Tim</firstname><surname>Newbold</surname><order>2</order></author><author><firstname>Adriana De</firstname><surname>Palma</surname><order>3</order></author><author><firstname>Sara</firstname><surname>Contu</surname><order>4</order></author><author><firstname>Samantha L.L.</firstname><surname>Hill</surname><order>5</order></author><author><firstname>Katia</firstname><surname>Sanchez-Ortiz</surname><order>6</order></author><author><firstname>Helen R.P.</firstname><surname>Phillips</surname><order>7</order></author><author><firstname>Lawrence N.</firstname><surname>Hudson</surname><order>8</order></author><author><firstname>Igor</firstname><surname>Lysenko</surname><order>9</order></author><author><firstname>Luca</firstname><surname>Borger</surname><orcid>0000-0001-8763-5997</orcid><order>10</order></author><author><firstname>J&#xF6;rn P.W.</firstname><surname>Scharlemann</surname><order>11</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling 2023-02-14T15:25:08.5578397 v2 39321 2018-04-06 Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project 8416d0ffc3cccdad6e6d67a455e7c4a2 0000-0001-8763-5997 Luca Borger Luca Borger true false 2018-04-06 SBI The PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) has collated ecological survey data from hundreds of published biodiversity comparisons of sites facing different land-use and related pressures, and used the resulting taxonomically and geographically broad database (abundance and occurrence data for over 50,000 species and over 30,000 sites in nearly 100 countries) to develop global biodiversity models, indicators, and projections. After outlining the science and science-policy gaps that motivated PREDICTS, this review discusses the key design decisions that helped it to achieve its objectives. In particular, we discuss basing models on a large, taxonomically, and geographically representative database, so that they may be applicable to biodiversity more broadly; space-for-time substitution, which allows estimation of pressure-state models without the need for representative time-series data; and collation of raw data rather than statistical results, greatly expanding the range of response variables that can be modelled. The heterogeneity of data in the PREDICTS database has presented a range of modelling challenges: we discuss these with a focus on our implementation of the Biodiversity Intactness Index, an indicator with considerable policy potential but which had not previously been estimated from primary biodiversity data. We then summarise the findings from analyses of how land use and related pressures affect local (α) diversity and spatial turnover (β diversity), and how these effects are mediated by ecological attributes of species. We discuss the relevance of our findings for policy, before ending with some directions of ongoing and possible future research. Book chapter Next Generation Biomonitoring: Part 1 58 201 241 Academic Press 9780128139493 00652504 Biodiversity intactness index, Alpha diversity, Beta diversity, Biodiversity indicators, Biodiversity models, Hockey-stick graph, Representativeness, Meta-analysis, 16 2 2018 2018-02-16 10.1016/bs.aecr.2017.12.003 http://www.sciencedirect.com/science/article/pii/S0065250417300284 COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University 2023-02-14T15:25:08.5578397 2018-04-06T00:06:49.2310091 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Andy Purvis 1 Tim Newbold 2 Adriana De Palma 3 Sara Contu 4 Samantha L.L. Hill 5 Katia Sanchez-Ortiz 6 Helen R.P. Phillips 7 Lawrence N. Hudson 8 Igor Lysenko 9 Luca Borger 0000-0001-8763-5997 10 Jörn P.W. Scharlemann 11
title Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project
spellingShingle Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project
Luca Borger
title_short Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project
title_full Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project
title_fullStr Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project
title_full_unstemmed Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project
title_sort Modelling and Projecting the Response of Local Terrestrial Biodiversity Worldwide to Land Use and Related Pressures: The PREDICTS Project
author_id_str_mv 8416d0ffc3cccdad6e6d67a455e7c4a2
author_id_fullname_str_mv 8416d0ffc3cccdad6e6d67a455e7c4a2_***_Luca Borger
author Luca Borger
author2 Andy Purvis
Tim Newbold
Adriana De Palma
Sara Contu
Samantha L.L. Hill
Katia Sanchez-Ortiz
Helen R.P. Phillips
Lawrence N. Hudson
Igor Lysenko
Luca Borger
Jörn P.W. Scharlemann
format Book chapter
container_title Next Generation Biomonitoring: Part 1
container_volume 58
container_start_page 201
publishDate 2018
institution Swansea University
isbn 9780128139493
issn 00652504
doi_str_mv 10.1016/bs.aecr.2017.12.003
publisher Academic Press
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
url http://www.sciencedirect.com/science/article/pii/S0065250417300284
document_store_str 0
active_str 0
description The PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) has collated ecological survey data from hundreds of published biodiversity comparisons of sites facing different land-use and related pressures, and used the resulting taxonomically and geographically broad database (abundance and occurrence data for over 50,000 species and over 30,000 sites in nearly 100 countries) to develop global biodiversity models, indicators, and projections. After outlining the science and science-policy gaps that motivated PREDICTS, this review discusses the key design decisions that helped it to achieve its objectives. In particular, we discuss basing models on a large, taxonomically, and geographically representative database, so that they may be applicable to biodiversity more broadly; space-for-time substitution, which allows estimation of pressure-state models without the need for representative time-series data; and collation of raw data rather than statistical results, greatly expanding the range of response variables that can be modelled. The heterogeneity of data in the PREDICTS database has presented a range of modelling challenges: we discuss these with a focus on our implementation of the Biodiversity Intactness Index, an indicator with considerable policy potential but which had not previously been estimated from primary biodiversity data. We then summarise the findings from analyses of how land use and related pressures affect local (α) diversity and spatial turnover (β diversity), and how these effects are mediated by ecological attributes of species. We discuss the relevance of our findings for policy, before ending with some directions of ongoing and possible future research.
published_date 2018-02-16T03:49:55Z
_version_ 1763752433064869888
score 11.037581

Similar Items