Brief description
The Macquarie Marshes, a Ramsar-listed wetland complex in northwestern New South Wales, represent one of Australia’s most significant inland floodplain ecosystems. This study synthesizes over a decade of ecological monitoring conducted under the Integrated Monitoring of Environmental Flows (IMEF) program, established in 1998 to evaluate the ecological outcomes of environmental water allocations. The primary objective was to quantify relationships between wetland water regimes—specifically flooding and drying cycles—and the diversity, abundance, and functional composition of ground cover vegetation.Lineage
The Macquarie Marshes IMEF groundcover vegetation data quality approach relied on strict standardisation and multi-level verification to ensure accuracy and consistency. Fieldwork followed Method 18, which used fixed transects and 1 m² quadrats positioned along 100 m lines to capture gradients from dry to wet zones, recording species presence, reproductive status, growth form, and percentage cover using the Braun-Blanquet scale. Unidentified plants were collected, pressed, and labeled for expert identification, supported by photographic records and GPS coordinates to guarantee site repeatability. Quality control was embedded through audit checklists, internal and external method reviews, and specimen verification against authoritative floras. Data were archived in regional technical files, entered into spreadsheets, and stored in the Triton database, with species lists compared across sampling occasions to detect inconsistencies. Analytical checks included ordination and indicator species analysis, while functional group classification provided an additional layer of logical validation. This integrated system of standardised protocols, rigorous documentation, specimen verification, and structured data analysis ensured high reliability of groundcover vegetation data for the Macquarie Marshes IMEF program.
Vegetation surveys were conducted along permanent 100 m transects using 5 m × 5 m quadrats at 10 m intervals, with species identified to genus and species level and classified into functional groups following Casanova and Brock and Casanova (1997), and related later papers by the same authors. Taxonomic validation was based on Plants of Western NSW (Cunningham et al., 1981). Monitoring occurred during three major phases: 2000 (Kidson et al. 2012), 2001–2006 (Knight, Driver and Knight 2007), and 2008–2010 (Driver, Driver and Michener 2010). Methodological refinements included adjustments to transect orientation to maintain perpendicularity to channels (Chessman, 2003; Chessman et al., 2007).
Across all sampling periods, vegetation composition exhibited strong site-specific patterns, with seasonal hydrology exerting greater influence than spatial variation. The inaugural year (2000) coincided with exceptionally wet conditions, resulting in high aquatic species prevalence (Kidson et al., 2012). Subsequent monitoring documented responses to managed environmental flows, including Wildlife Allocation releases and targeted replenishment events (Love, 2004; Baker, 2003). Notably, groundcover species such as Paspalum distichum (Water Couch) and Typha domingensis (Cumbungi) demonstrated positive responses to inundation, while the decline of Phragmites australis indicated potential long-term impacts on River Red Gum health (Driver & Knight, 2007; Driver & Michener, 2010).
Environmental flow interventions varied in effectiveness due to hydrological constraints, transmission losses, and antecedent drought conditions. Reports from 2005–06 and 2009–10 highlighted improved vegetation condition and biodiversity outcomes following substantial flow deliveries (~84,000 ML), with ancillary benefits for bird breeding and wildlife abundance (Driver & Knight, 2007; Driver & Michener, 2010). However, analyses underscore the complexity of attributing ecological responses solely to flow events, given confounding factors such as rainfall variability and grazing pressure.
This dataset, now historical, provides critical insights for adaptive water management under NSW Water Sharing Plans and informs contemporary programs such as Flow-MER (Driver et al., 2013). Data accuracy was maintained through rigorous field protocols and cross-validation during entry, though caution is advised regarding interpretation of zero values in early field sheets (Knight phase).
Notes
CreditWe at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
The purpose of this dataset is to support evaluation of how environmental water allocations influence wetland vegetation in the Macquarie Marshes. It was collected under the IMEF program to link flooding and drying cycles with plant diversity and abundance, assess the effectiveness of flow management, and provide long-term evidence for adaptive water planning and conservation of inland wetlands.
Data Quality Assessment Scope
local :
dataset
The Macquarie Marshes IMEF groundcover vegetation data quality approach relied on strict standardisation and multi-level verification to ensure accuracy and consistency. Fieldwork followed Method 18, which used fixed transects and 1 m² quadrats positioned along 100 m lines to capture gradients from dry to wet zones, recording species presence, reproductive status, growth form, and percentage cover using the Braun-Blanquet scale. Unidentified plants were collected, pressed, and labeled for expert identification, supported by photographic records and GPS coordinates to guarantee site repeatability. Quality control was embedded through audit checklists, internal and external method reviews, and specimen verification against authoritative floras. Data were archived in regional technical files, entered into spreadsheets, and stored, with species lists compared across sampling occasions to detect inconsistencies. Analytical checks included ordination and indicator species analysis, while functional group classification provided an additional layer of logical validation. This integrated system of standardised protocols, rigorous documentation, specimen verification, and structured data analysis ensured high reliability of groundcover vegetation data for the Macquarie Marshes IMEF program
Wetlands Project-Hypothesis 7-Macquarie Groundcover Vegetation
uri :
https://www.data.gov.au/data/dataset/nsw-hefm-imef-wetlands-project-hypothesis-7-macquarie-groundcover-vegetation
Data Quality Assessment Result
local :
Quality Result
Please see description of QA
Created: 2008-10-30
Issued: 2025-03-31
Modified: 2026-06-01
Data time period: 2000-01-15 to 2010-02-12
text: The IMEF Macquarie Marshes survey sites use the GDA94 / MGA Zone 55 coordinate system. The bounding box for these sites is defined by the following extremes: the northern limit at Ginghet Swamp with a northing of 6,661,000 metres, the southern limit at Oxley Station Lagoon with a northing of 6,557,835 metres, the eastern limit at Terrigal Creek IMEF Site with an easting of 567,942 metres, and the western limit at Buckiinguy Swamp with an easting of 546,652 metres.
User Contributed Tags
Login to tag this record with meaningful keywords to make it easier to discover
Point-of-truth metadata URL
Plants of Western New South Wales.
uri :
https://www.publishing.csiro.au/book/6772/
Plant life at the edge of wetlands: ecological responses to wetting and drying patterns
doi :
https://doi.org/10.13140/2.1.2761.5367
IMEF Methods Manual (IMM00a). NSW Department of Land and Water Conservation
Wetland Vegetation Survey – Large Wetlands. - Baker, T. (2003). Marshes Wildlife Allocation Report
Operation and Performance Report 2002–03: Macquarie Marshes Water Management Plan
Macquarie Marshes Environmental Flow Responses of Groundcover Plants to Environmental Flow
Ecological monitoring to support Water Sharing Plan evaluation and protect wetlands of inland New South Wales, Australia
- URI : geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/9eab3e52-5c81-45bd-98fd-2b48dde3bbf2
- global : 9eab3e52-5c81-45bd-98fd-2b48dde3bbf2
