Search the EPA Research Database

Project Search Result

Project Code [2021R529]

This information is correct as of today and is updated from time to time by the EPA to reflect changes in the management of the project. Please check back regularly for updates.

Project title

StableGrass

Primary Funding Agency

DAFM

Co-Funding Organisation(s)

n/a

Lead Organisation

University College Cork (UCC)

Lead Applicant

n/a

Project Abstract

Irish grasslands can roughly be divided into intensively used, frequently reseeded improved grasslands and semi-natural grasslands which are typically under extensive agricultural use (grazing or hay cutting) but harbour greater biodiversity. While increased plant species diversity has generally been shown to improve carbon storage and yield stability in response to climatic stress, little is known about the capacity of Irish semi-natural grasslands to store carbon and their temporal yield stability, or how plant diversity affects these aspects. Diversity is not only reflected in the number of species but also in the diversity of functional traits. For example, deep-rooting plants result in more stable carbon storage deeper down in the soil and are more stress tolerant, but plants with less extensive root systems may have higher above-ground yield. Leaf traits can also directly indicate the strategy of a plant or a community, such as stress tolerance or competitiveness (associated with rapid growth). This project addresses the important question of how plant diversity affects below-ground carbon storage and the stability of herbage production in response to climate-related stress. Building on the NPWS Irish Semi-natural Grasslands Survey (2007-2012), this study will select suitable grassland sites and determine their plant diversity at species and functional level in field surveys. It also will conduct carbon audits to determine the profiles of carbon storage in the soil and relate them to plant (functional) diversity. High-resolution satellite imagery will be used to classify grasslands and determine their biodiversity through remote sensing. The latest advancements in satellite and unmanned aerial vehicle (UAV) will be used for data acquisition and machine learning approaches to develop methods for monitoring yield and plant functional diversity, with the aim of predicting yield stability at national level. Research outputs will inform policy on the priorities for the protection of semi-natural grassland habitats.

Grant Approved

�383,641.31

Research Hub

n/a

Research Theme

Carbon Stocks, GHG Emissions, Sinks and Management Options

Start Date

01/10/2022

Initial Projected Completion Date

30/09/2025