A proposed framework for a social-ecological traits database for studying and managing urban plants and assessing the potential of database development using Floras
Year: 2023
Type: article
Abstract: Trait-based frameworks have received increased attention in biodiversity research for their capacity to streamline extensive and complex information for policy and management purposes. Such frameworks, however, are mostly developed for natural ecosystems, and social-ecological dynamics in urban ecosystems may present needs that are distinct from natural ecosystems. We proposed a framework for developing a social-ecological traits database for plant selection and spontaneous vegetation management, and examined the potential of using Floras, a resource available in most regions of the world, for database development. The Flora of Taiwan and vascular plants previously identified in Taipei city parks were used as a case study. Three major issues were found using Flora data: 1) systematic omission of horticultural species, 2) low species trait coverage, and 3) complexity in original data. We also compared the framework to the Flora-informed database and two global trait databases, TRY and GIFT. TRY included more measurement-based traits than Flora and were imperative to functional interpretations; Flora had wider global coverage than TRY. GIFT was based on Floras, but included only functional traits and omitted traits of social importance identified in our framework. Information uniquely available in the Flora include information of local relevance (e.g. associated local landscapes and commonness/rarity within the region) and social aspects of ecosystem services (e.g., edibility and visual aesthetics). Maintenance considerations are lacking in all three databases. We suggest interdisciplinary collaboration to further advance the proposed social-ecological traits framework and database to enhance the functions and sustainability of urban green infrastructures.
Source: Urban forestry & urban greening
Institution: Chinese Culture University
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,330
Awards: G2081952749, G4371958483, G5406120769
OpenAlex ID: W4389431069
