In 2014, the International Union for Conservation of Nature adopted the Red List of Ecosystems (RLE) criteria as the global standard for assessing risks to terrestrial, marine, and freshwater ecosystems. Five years on, it is timely to ask what impact this new initiative has had on ecosystem management and conservation. In this policy perspective, we use an impact evaluation framework to distinguish the outputs, outcomes, and impacts of the RLE since its inception. To date, 2,821 ecosystems in 100 countries have been assessed following the RLE protocol. Systematic assessments are complete or underway in 21 countries and two continental regions (the Americas and Europe). Countries with established ecosystem policy infrastructure have already used the RLE to inform legislation, land-use planning, protected area management, monitoring and reporting, and ecosystem management. Impacts are still emerging due to varying pace and commitment to implementation across different countries. In the future, RLE indices based on systematic assessments have high potential to inform global biodiversity reporting. Expanding the coverage of RLE assessments, building capacity and political will to undertake them, and establishing stronger policy instruments to manage red-listed ecosystems will be key to maximizing conservation impacts over the coming decades.
In: Gallagher , R V , Falster , D S , Maitner , B S , Salguero-Gómez , R , Vandvik , V , Pearse , W D , Schneider , F D , Kattge , J , Poelen , J H , Madin , J S , Ankenbrand , M J , Penone , C , Feng , X , Adams , V M , Alroy , J , Andrew , S C , Balk , M A , Bland , L M , Boyle , B L , Bravo-Avila , C H , Brennan , I , Carthey , A J R , Catullo , R , Cavazos , B R , Conde , D A , Chown , S L , Fadrique , B , Gibb , H , Halbritter , A H , Hammock , J , Hogan , J A , Holewa , H , Hope , M , Iversen , C M , Jochum , M , Kearney , M , Keller , A , Mabee , P , Manning , P , McCormack , L , Michaletz , S T , Park , D S , Perez , T M , Pineda-Munoz , S , Ray , C A , Rossetto , M , Sauquet , H , Sparrow , B , Spasojevic , M J , Telford , R J , Tobias , J A , Violle , C , Walls , R , Weiss , K C B , Westoby , M , Wright , I J & Enquist , B J 2020 , ' Open Science principles for accelerating trait-based science across the Tree of Life ' , Nature Ecology & Evolution , vol. 4 , pp. 294–303 . https://doi.org/10.1038/s41559-020-1109-6
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.
In: Gallagher , R V , Falster , D S , Maitner , B S , Salguero-Gómez , R , Vandvik , V , Pearse , W D , Schneider , F D , Kattge , J , Poelen , J H , Madin , J S , Ankenbrand , M J , Penone , C , Feng , X , Adams , V M , Alroy , J , Andrew , S C , Balk , M A , Bland , L M , Boyle , B L , Bravo-Avila , C H , Brennan , I , Carthey , A J R , Catullo , R , Cavazos , B R , Conde , D A , Chown , S L , Fadrique , B , Gibb , H , Halbritter , A H , Hammock , J , Hogan , J A , Holewa , H , Hope , M , Iversen , C M , Jochum , M , Kearney , M , Keller , A , Mabee , P , Manning , P , McCormack , L , Michaletz , S T , Park , D S , Perez , T M , Pineda-Munoz , S , Ray , C A , Rossetto , M , Sauquet , H , Sparrow , B , Spasojevic , M J , Telford , R J , Tobias , J A , Violle , C , Walls , R , Weiss , K C B , Westoby , M , Wright , I J & Enquist , B J 2020 , ' Open Science principles for accelerating trait-based science across the Tree of Life ' , Nature Ecology and Evolution , vol. 4 , no. 3 , pp. 294-303 . https://doi.org/10.1038/s41559-020-1109-6
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.