Transect-based surveys of riparian restoration projects, May 2017 to April 2018 (NESP TWQ 3.1.4, CSIRO)

This dataset presents two excel spreadsheets containing the transect-based estimates of biomass carbon and condition score of study sites. The health of the Great Barrier Reef (GBR) is threatened by excessive delivery of sediments (and the pollutants they carry) to the marine environment. Remediation of riparian vegetation is considered an important mechanism for reducing stream bank erosion, improving water quality, and subsequently GBR health outcomes. But despite previous investments in such projects, there is a paucity of information on whether previous investments have been successful in delivering these benefits, and what mechanisms or incentives could be refined to better facilitate success. To help fill this knowledge gap, this study undertook three activities. 1. Project-scale success. Explore the success of previous investments through both field-based assessments of improved water quality (as indicated by a Condition Score), and face-to-face semi-formal social surveys of landholders. 2. Catchment-scale success. Review of requirements for widespread landholder participation and whether this implies merit in alternative incentive schemes. 3. Expanding the metrics of success. Quantify co-benefits through field-based assessments of biodiversity (as indicated by Plant Cover index and landscape-scale metrics of project size and connectivity) and carbon mitigation. To gain some insight into whether previous investments in riparian remediation projects have been successful, field assessments were undertaken at 41 project areas of known age and management regime (see Table 3 of final report, Paul et.al. 2018). These included both revegetation and regeneration project types undertaken in areas of land used for either cropping (sugarcane or bananas), cattle grazing (of a range of intensities), or urban development. The ages of the projects ranged from 3–35 years. For six study sites with relatively low stocking density and/or small size, the entire project area was assessed. For all other study sites, 5–32 transects were used for assessment, depending on the size of the project area. All transects were 5 m width. But transect lengths varied (between 3–221 m) within and between sites based on the width of the riparian project area, with total transects lengths measured varying from 100 m in relatively small sites to up to 2,236 m in relatively large sites (see Table 3 and Figure 1 of final report, Paul et.al. 2018). Methods Condition score: Although it was beyond the scope of this study to measure the influence of the riparian remediation project on water quality per se, the Tropical Rapid Appraisal of Riparian Condition (TRARC, Dixon et al. 2006) assessment was used as a simple surrogate of this. TRARC provides 24 scores from transect-based visual assessment that are grouped into indices of condition of the riparian zone. These are grouped into four indices- each contributing a maximum value of 25 (see Figure 2 in final report, Paul et.al. 2018). These four indices then sum to derive the overall condition score (maximum value of 100). Other ‘disturbance’ factors, such as measure of average riparian buffer width when compared to average stream width (i.e. Tree Clearing), were also assessed to derive the TRARC Pressure Score (also a maximum value of 100), see Figure 2 in final report, Paul et.al. 2018)). These visual assessment scores were obtained for the lower, mid and upper reaches of each transect measured at the dry tropics study sites, with the weighted average values of indies and scores being derived in accordance with the relative contribution of each of these sections to the total width of the project. This was done for the study sites assessed in the Upper Fitzroy and Dawson sub-regions. But given their generally smaller size and more uniform characteristics, visual assessment scores for the study sites in the Cairns Coastal, Atherton Tablelands and Mary sub-regions were noted as a subjective weighted average for the project area. We explored whether there was any indication that the trends for increased Condition Score with project age differed between revegetation and regeneration projects, and particularly, the grazing intensity of the study sites. We also explored which indices of the Condition Score tended to contribute to this increase in both revegetation and regeneration project types. Carbon storage and typical rates of sequestration of carbon: At each of the field assessment sites, stem diameters were measured for all trees and shrubs within each of the randomly placed transects, or for six study sites, the entire project area (see Table 3 of final report, Paul et.al. 2020). For all 41 sites where stem diameter measurements were made, estimates of biomass carbon were made based on the assumption that about 50% of both above-ground biomass (AGB) and below-ground biomass (BGB) is comprised of carbon (Gifford et al. 1999, 2000). To estimate AGB and BGB, we utilised allometric equations that predict biomass based on stem diameter. Such equations have been developed for the main plant functional types in Australia (Paul et al. 2016, 201b), with these being deemed appropriate to apply to trees or shrubs from the wet tropical, dry tropical and subtropical GBR catchments given these equations were derived based on 124 (129), 472 (36) and 737 (57) individual trees or shrubs sampled for ABG (and BGB) from these regions of Queensland, respectively. The total allometry-predicted biomass of all trees and shrubs within each transect was summed, and expressed on a per area basis. This was done separately for remnant and younger regenerated or planted trees or shrubs. These results were then used to estimate the average (± standard error) biomass, and biomass carbon stocks, within all woody vegetation in each riparian remediation project. However, rates of sequestration of biomass in carbon were calculated by considering only the regenerating or planted trees and shrubs within each site given any carbon stocks in pre-existing remnant vegetation was assumed to represents the baseline carbon stock that existed prior to the project commencing. Although additional accumulation of biomass carbon in remnant trees is possible post-project establishment, measurement of this was beyond the scope of the project as longer term monitoring would be required. In the revegetation stands assessed in the wet tropics or subtropics, remnant trees could generally be visually distinguished from the younger planted trees. However, there was often some uncertainty in this categorisation. Moreover, for stands where there was natural regeneration in the eucalypt woodland regions studies in the dry tropics, remnant trees were often numerous and could not be visually distinguished from the younger regenerating trees. However, diameter frequency distributions, assessed on site-by-plant functional type basis, revealed skewing towards the smaller size classes. Hence for regeneration stands, the conservative assumption was made that all individuals greater than the 85th percentile diameter size were remnant individuals, while those smaller than this were assumed to be regeneration attributable to the project. We also explored the impact of assuming this cut off was the less conservative 95th percentile. Similarly, in revegetation stands, we also explore the impact of categorising remnant trees by size class (using both the 85th and 95th percentile) rather than relying on the subjective visual assessment for signs of senesces due to old age. Taking into account the uncertainty in estimates of biomass carbon, we explored whether there was evidence of increases in biomass carbon with increasing age of the remediation projects, and whether this differs between revegetation and natural regeneration project types. Estimates were also provided for typical rates of sequestration of carbon in these various project types. Given the management regime tended to be related to the bioclimatic region (e.g. revegetation projects are common in the wet tropics while natural regeneration projects are common in the dry tropics), this confounded our dataset. It was therefore not statistically viable to assess the impact on biomass carbon of factors such as the bioclimatic region, or whether or not the stand was grazed. Limitations of the data: The TRARC Condition Score is designed to indicate the condition with respect to intact and undisturbed vegetation. It therefore will provide an indication of the extent to which a riparian remediation project has approached full rehabilitation. Clearly full rehabilitation may not be necessary to maximise the impact of riparian remediation on improved water quality outcomes, e.g. some weeds can be beneficial in reducing stream bank erosion. However, it was beyond the scope of this study to develop a refined condition score that reflects these impacts more directly. Format: This dataset presents two excel spreadsheets: Transect for biomass carbon assessment.xlsx and Transects of Condition Score.xlsx Data Dictionary: Transect for biomass carbon assessment.xlsx TAB -Details of sites SITE ID - unique identification number for site [total 41] REGION - the region is which the site is located [Cairns Coastal, Atherton Tableland, Dawson River Catchment, Upper Fitzroy, Mary River SITE NAME - name of the site which the study took place LATITUDE- decimal degrees to two decimal places LONGITUDE - decimal degrees to two decimal places AGE OF THE PROJECT (YEARS) - duration in years since the restoration project originally commenced [between 3 and 35 years] TYPE OF PROJECT - indicated the type of restoration from original project [Planted (revegetation), Regen (regeneration)] TAB - Inventory [Cairns Coastal, Atherton Tablelands, Dawson River& Upper Fitzroy, Mary River] ID - unique id for row entry 1 - year of original restoration project (correlates with ‘AGE OF PROJECT’ column in Details of Sites tab) SITE -site number where transect is located, corresponds to SITE ID. TRANSECT - number of transect or 'all' (at sites where whole site was assessed). Multiple measurements for a single transect, each row represents one tree in the transect. . BEARING - unit of measurement is degrees, where recorded WIDTH (m) - width of transect where recorded. TRANSECT LENGTH (m) - length of transect in meters where recorded. Where whole site has been assessed, total area is recorded only AREA (Ha) - total area of transect calculated by multiplying width (x) length, dividing (/) by 10000 or where column TRANSECT lists ‘all’, AREA (Ha) is entered as a single figure. ALLOMETRIC CALCULATIONS FOR BIOMASS dry matter (DM) Estimated biomass per individual tree, shrub, etc AGB (kg DM), assuming Eu - above ground biomass transect, assuming Eucalyptus species, measured in kilograms of dry matter. AGB (kg DM), assuming Other-H - total above ground biomass per transect, assuming Other -H species, measured kilograms of dry matter. BGB (kg DM), assuming Euc - below ground biomass per transect, measured in kilograms of dry matter. Estimated biomass per TRANSECT (area) (calculated by sum of AGB(kg) or BGB(kg) measurements for transect, divided (/) by 1000, relative to transect area by dividing by Area(ha) value. AGB (t DM/ha), assuming Euc - total above ground biomass of dry matter per hectare, assuming Eucalyptus species, measured in tonnes AGB (t DM/ha), assuming Other-H - total above ground biomass of dry matter per hectare, assuming Other -H species, measured in tonnes BGB (t DM/ha), assuming Euc - Total below ground biomass of dry matter per hectare, measured in tonnes POSITION - location of tree within transect site, where recorded SECTION LENGTH (m) - duplicate of transect length in meters FORM - in tab [Rocky Inventory] abbreviation of adjacent FORM column T, S, * (contains * indicating data was not available) FORM - describes the vegetation [tree, shrub, palm, remanent, cas (casuarina), DT (dead tree), fig (Fig Ficus), mel (melaleuca?), dead shrub.. DHT - height of diameter measurement. Trees, palms and remanent are measured at 130cm, while shrubs at 10cm. Some DHT Mary River tab at site Eales Regen contain (*) entries eqvD10(cm) – where DHT is 10, data is result of equation in column SumD^2 eqvD130(cm) – where DHT is 130, data is result of equation in column SumD^2 Diameter measurements – as measured at relevant DHT height. There were up to 10 stem diameters per individual tree or shrub. D1 (mm) – diameter of tree/shrub at height specified in column DHT, in millimetres, first reading D2 (mm) - where applicable, second reading D3 (mm) - where applicable, third reading D4 (mm) - where applicable, forth reading D5 (mm) - where applicable, fifth reading D6 (mm) - where applicable, sixth reading D7 (mm) - where applicable, seventh reading D8 (mm) - where applicable, eighth reading D9 (mm) - where applicable, ninth reading D10 (mm) - where applicable, tenth reading Estimate of volume using relevant diameter reading (Calculated by the relevant diameter reading (1-10), divided by 10, multiplied by the second power. D1^2 (cm) - calculation of first diameter reading D2^2 (cm) - where applicable second diameter reading D3^2 (cm) - where applicable third diameter reading D4^2 (cm) - where applicable, forth diameter reading D5^2 (cm) - where applicable, fifth diameter reading D6^2 (cm) - where applicable, sixth diameter reading D7^2 (cm) - where applicable, seventh diameter reading D9^2 (cm) - where applicable, eighth diameter reading D9^2 (cm) - where applicable, ninth diameter reading D10^2 (cm) – where applicable, tenth diameter reading Estimate of total volume using D^2 calculations SUMD^2 - sum of columns of D^2 (cm), divided (/) by square root calculation (SQRT) References: Dixon, I., M. Douglas, J. Dowe, and D. Burrows. 2006. Tropical rapid appraisal of riparian condition version 1 (for use in tropical savannahs). River and Riparian Land Management Technical Guideline, 7, 1–36. Cook-Patton, S.C., Leavitt, S.M., Gibbs, D. et al. Mapping carbon accumulation potential from global natural forest regrowth. Nature 585, 545–550 (2020). https://doi.org/10.1038/s415...20-2686-x Gifford R.M. (2000) Carbon contents of above-ground tissues of forest and woodland trees. National Carbon Accounting System, Technical Report No. 22, Australian Greenhouse Office. September 2000. 24p. Gifford R.M. (1999) Carbon content of woody roots. National Carbon Accounting System Technical Report No 7, Australian Greenhouse Office. November 1999. 10p. Paul KI, Roxburgh SH, Chave, J. et al. (2016) Testing the generality of above-ground biomass allometry across plant functional types at the continent scale. Global Change Biology, 22, 2106-2124. Paul KI & Roxburgh SH. (2020) Predicting carbon sequestration of woody biomass following land restoration. Forest Ecology and Management 460:117838 Paul KI, Larmour, J., Specht, A., et al. (2018) Testing the generality of below-ground biomass allometry across plant functional types at the continental scale. Global Change Biology. In review. Paul, K.I., Bartley, R. Larmour, J.S, Micah J Davies, Debbie Crawford, Shane Westley, Bart Dryden, Cassandra S James (2018). Optimising the management of riparian zones to improve the health of the Great Barrier Reef. Report to the National Environmental Science Program. Reef and Rainforest Research Centre Limited, Cairns (79 pp.). https://nesptropical.edu.au/...eport.pdf Data Location: This dataset is filed in the eAtlas enduring data repository at: data\nesp3\3.1.4-Riparian-zone-management

Principal Investigator
Paul, Keryn, Dr CSIRO Land and Water
Co Investigator
Bartley, Rebecca, Dr CSIRO Land and Water
Point Of Contact
eAtlas Data Manager Australian Institute of Marine Science (AIMS) e-atlas@aims.gov.au

Data collected from 01 May 2017 until 30 Apr 2018


Data Usage Constraints
  • Attribution 3.0 Australia