Climate and Biodiversity Credentials for Australian Grass-Fed Beef: A Review of Standards, Certification and Assurance Schemes

Abstract

Extensive livestock production occupies 25% of the ice-free terrestrial surface of the Earth, and Australian beef production contributes about 10% of this total land footprint. Therefore, the management of cattle has major implications for natural vegetation, soils, biodiversity, and atmospheric greenhouse gases in Australia and globally. To meet global sustainability targets and consumer expectations, a variety of environmental Standards, Certification and Assurance (SCA) schemes are being developed and implemented to enable producers to verify claims relating to their products. Improved standardization and coordination are now needed to address the rapid proliferation of credentialing systems that use different frameworks, methods and levels of scientific verification. Using the Australian grass-fed beef industry as a case study, we identified the measures, metrics and methods that are currently used by SCA schemes for climate and biodiversity credentialing. From here, a co-design process with industry representatives was applied to develop recommendations for credentialing in extensive beef production, feedlots and meat processing. It was clear that the successful adoption of credentialing by beef producers will require flexible and user-friendly support tools that use scalable data sources such as existing producer records, agtech databases and remote sensing information. Substantive rewards and incentives will be required to support producer engagement with the SCA schemes. Overall, ’more needs to be done to ensure the transparency of schemes and to meet benchmarks for integrity such as determining uncertainty and support though peer-reviewed science.

1. Introduction

Market incentives based on the demonstration of sustainable food production practices are increasingly used as one of few options to drive positive changes in the way food is produced and distributed globally. Reducing net emissions of greenhouse gases (GHG) and preserving ecosystem biodiversity are two central objectives of sustainable agricultural production. These two concepts are fundamentally connected through land management practices but have been largely addressed independently by the industry, whereas a more integrated approach may be beneficial to tackle this challenge globally and domestically [1]. Increasing the market orientation of the livestock sector acts to motivate more sustainable approaches to production, in addition to mitigation, as a result of consumer expectations [2]. As public discussion on the environmental sustainability of agriculture intensifies, consumers are becoming more interested in the provenance and labeling of the products they purchase and are increasingly wary of product “greenwashing” [3]. However, consumers have a wide range of priorities and are unlikely to drive the magnitude of change that is needed on the back of their purchasing decisions alone [4]. The evolution of policy toward climate and biodiversity objectives in Australia and internationally [5,6], as well as the associated need for the beef supply chain to protect its reputation, has seen a rise of Standards, Certification and Assurance schemes emerge in various parts of the supply chain, particularly in the private sector [7].

In Australia, the Emissions Reduction Fund (ERF) [8] offers landholders, communities and businesses the opportunity to run projects in Australia that avoid the release of greenhouse gas emissions or remove and sequester carbon from the atmosphere. Successful participants in these projects can earn Australian carbon credit units (ACCUs), where each ACCU represents one tonne of carbon dioxide equivalent (tCO₂-e) emissions stored or avoided by a project. ACCUs can be sold to generate income, either to the Australian government through a carbon abatement contract or to companies and other private buyers in the secondary market. Contrasting the expansion of credentialing in the agricultural industry, there is relatively little published research examining the effectiveness, design principles, and potential pitfalls toward successful development and implementation. More work is needed to ensure that the underlying principles, technologies and practices will achieve their intended objectives and that the credentials are based on suitable measures and metrics to incentivize a change in the practices of grass-fed beef businesses when this is required [9].

Despite the high risks to business as usual that are currently being faced in the beef industry, such as social licence and access to markets, the basic underpinning science to support the development of standards and credentialing schemes in the beef industry is lacking. The many SCA schemes becoming available to beef producers through market opportunities vary widely in their scope and design. Currently, there is increasing complexity in the sustainability standards, certification, and accreditation initiatives due to the proliferation of competing and often overlapping programs, and consideration is being given to better coordination across schemes [10]. For example, the Australian Agricultural Sustainability Framework has indicated that it may act as a centralized “marketplace” for assessing certification schemes [10]. This situation has also been recognized internationally for some time, where “global trade and the governance of inter-state externalities on public goods compounded by the proliferation of sustainability schemes, call for a multi-party co-operation that must be supported by ‘common rules’ in order to reduce fragmentation, prevent conflicts, mitigate uncertainty, and build capacities for effective sustainability” [11].

In this review, we aim to bring together industry experience and supporting research to analyze the key characteristics of the current SCA schemes applicable to extensive beef production. The review provides some coverage of global regions, a range of agricultural industries, supply chain segments, target outcomes, accreditation methods, measures and data sources, and scale. We explore how the various schemes have approached quantifying key metrics that have been used in credentialing. The structure of the review considers the range of ways that the beef supply chain engages in credentialing through the mitigation of total and per-unit-production GHG emissions, carbon sequestration, and managing land to support biodiversity. Australian beef supply chains are complex and highly varied [12], so developing credentials requires careful design and flexibility so that they can be applied broadly across the industry. For example, the practices of grain feeding to support year-round feeding and finishing cattle to meet market specifications vary widely. In one study, grass-finished cattle required 0.85 t of feed (for maintenance) purchased for the farm system, compared with 2.25 t for 150-day grain-finished cattle per tonne of liveweight produced [13]. Differences in grain feeding affect the methane (CH₄) intensity of production but also affect other sustainability measures such as the Net Protein Contribution of beef production for human diets [13]. The ongoing contribution of beef production and the design of production systems have many moving parts. In this review, we have focused on two areas of high priority: the effects of extensive beef production on GHG emissions and biodiversity.

The objective of the review was to support improvements in the methods and coordination of climate and biodiversity credentials in the Australian grass-fed beef industry. Guided by a review of relevant SCA schemes and a review of the scientific literature and through consultation with industry leaders through project workshops, we recommend underpinning principles and methods to inform the development and implementation of credentialing schemes for the Australian beef industry.

2. Review of Current SCA Schemes

To provide coverage of existing SCA schemes, we organized the review into sections addressing (i) the quantification of emissions (total emissions and emissions intensity), (ii) sequestration (carbon capture within the agro-ecosystem), and (iii) credentials for the provisioning of ecosystem services via climate and biodiversity for either credentialing of their own product within the supply chain or on-selling the credits within emerging markets. The review covers 68 Australian and 40 international SCA schemes or their components [10,11,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120]. A summary of the schemes evaluated is provided as Supplementary Material.

3. Total Emissions

The GHG emissions from beef production globally are predominantly from the net production of enteric CH₄, nitrous oxide (manure and fertilizer application) and carbon dioxide (feed and land use change, particularly deforestation) [121]. Estimates for beef production in Australia reflect these emission sources, with an estimated 48% from enteric CH₄, 40% from land use change and 8% from soil management practices, with the remaining ~4% mostly comprising energy use, processing emissions and manure management [9]. Based on this, the management of enteric CH₄ emissions and maintaining or increasing on-farm stored carbon stocks should be the primary focus for reducing emissions in grass-fed beef enterprises. Accounting frameworks for the contribution of the different GHG emissions to global warming continue to develop, with ongoing discussion around the metrics and factors that are used to establish equivalence between them. A summary of the current approaches for calculating GHG fluxes is provided in the Greenhouse Gas Protocol Agricultural Guidance [14]. The GWP100 climate metric is commonly used, but its usefulness in credentialing livestock production has been questioned because each of the GHGs varies in its radiative efficiency and atmospheric lifetime [122]. The potential for a change in GHG emissions accounting methods is a significant additional challenge to the implementation of SCA schemes and poses a risk that will likely deter the taking-up of credentialing in the livestock industry.

The various metrics and measurements associated with determining total emissions and emissions intensity from grass-fed beef production within SCA schemes are presented in

Table 1. Summary of measures used by SCA schemes to determine total GHG emissions and emissions intensity for grass-fed beef production.

Metric	Method or Data Source	Method Specification	References
Livestock
Resident herd/flock	Farm records	Count by Class (n)	[14,25,27,28,40]
	Farm records	Class LW (kg), LWG (kg d−1) by season
	Expert tables	SRW (kg) published data
Cows calving rate		% by season	[25,28]
Traded stock (Bought and sold)	Farm records	By class, LW by season	[25,28]
Feed and pasture
Forage Quality	Farm records Expert tables published data	Forage DMD (%) and CP (%) by season	[14,25,27,28,40]
Supplementary feeds	Farm records	Type, Amount, DMD and CP%	[14,25,27]
Grazing duration	Farm records	Days at pasture (d)	[28]
Supplementation period	Farm records	Days feeding (d)	[28]
Feed additives (minerals & licks)	Farm records	Type, Amount (kg)	[14,25,27,29]
Feedlot (Domestic, Export, Mid-fed, Long-fed)
Livestock factors	Feedlot records Expert tables	Count by class (n), Days on feed (d), Class LW (kg), Class LWG (kg d−1), N retention (%)	[27,29,40]
Diet factors	Feedlot records Expert tables	DMD (%),	[27,29,40]
		Crude protein (%),
		Net Energy (MJ kg−1), Soluble residue,
		Hemi-cellulose (%)
		Cellulose (%)
Waste factors	Expert tables	Allocation: Stockpile Composting, Direct application, Effluent ponds	[27,29,40,123,124,125]
Crop production for fodder
Residue biomass			[14]
Fertilizer and chemicals (pasture)
Type of fertilizer	Farm Records	Composition (%), Rate (kg ha−1), (t)	[14,23,25,29]
		Method (direct, indirect)
		Timing (dates)
Herbicides/pesticides/animal health	Farm Records	Rate–vol (L) or ai (kg)	[25,27]
Fuel and electricity
Purchased electricity	Farm Records	State grid (kWh)	[14,23,25,29]
Renewable electricity	Calculation	Used on-farm (kWh)	[14,23,25,29]
		Sold to the grid (kWh)
Fuel consumption Stationary or transport	Farm Records	Diesel (L y−1) Petrol (L y−1)	[14,23,25,29]
Transport and distribution	Calculation	etd Distance (km), Engine type	[23]
Processing	Calculation	eP	[23]
Soil and vegetation management of emissions
Land use change and deforestation	Calculation	Carbon stock (kg C ha−1)	[23]
		Yield raw (t ha−1 y−1)
		Accumulation period (y)
Area of residues burned	Calculation	Total area (ha) Residue type	[14]
Savanna burning		Total area (ha), Rainfall zone, Vegetation code & class, Patchiness, Fuel class, Years of fuel load (y)	[25]

Abbreviations: CP, crude protein; DMD, dry matter digestibility; ai: active ingredient, e_P, emissions from processing_; e_td, emissions from transport and distribution_; LW, live weight; LWG, live weight gain; N, nitrogen; SRW, standard reference weight.

. This includes a brief specification of methods and any associated references that provide scientific support and verification.

Calculations of GHG emissions tend to be considered within the system boundary of a supply chain element rather than the whole supply chain [23]. In the case of grass-fed beef production, this would typically be at the business level, with grazing, lot feeding and processing businesses or some combination in some cases. Group certification may also be acceptable in cases where units are very similar [23], although this may preclude activities within individual businesses to improve their emissions profile.

The GHG Protocol Agricultural Guidance [14], produced by the World Resources Institute (WRI) and the World Business Council for Sustainable Development (WBCSD), is internationally recognized and used by entities (producers or businesses) seeking to develop an inventory of agricultural GHG emissions [14]. As shown in Table 1, ref.[14] covers a wide range of metrics within an inventory. The GHG Protocol Agricultural Guidance is a supplement to the GHG Protocol Corporate Accounting and Reporting Standard [126], which was initially launched in 1998 with the intention of identifying industry-accepted best practices for GHG accounting and reporting but did not cover agricultural emissions. These guidelines do not provide methods for project- or product-level accounting, and the calculator tool that is available is generic and difficult to adapt to beef production systems.

The Sheep and Beef GHG Accounting Framework (SB-GAF) [25] is currently the most detailed and peer-reviewed supported tool for estimating GHG emission profiles of beef production in Australia. However, in the current format, the level of complexity may still be too high for business-level adoption, and projects are currently under way to improve its accessibility to producers. Several variants of the SB-GAF calculator have been launched as web-based applications since 2021 by Meat and Livestock Australia [127] and consultancy groups (e.g., Ruminati [57]) with the aim of simplifying some of the data entry complexity, in particular the seasonal assessments of pasture quality, in order to accelerate stakeholder engagement. It is unclear at present how these simplified variants will be accepted under the official ERF if they are to be used beyond entry-level adoption. The ERF has its own calculator, the beef cattle herd management calculator [18]. The cross-validation of these calculator variants would also be needed to add confidence to potential users. As with SB-GAF, continuity in the version control will be necessary to not adversely impact benchmarking endeavors. The Feedlot GHG Accounting Framework (F-GAF) [29] is the equivalent calculator for GHG emissions from Australian feedlots.

Some existing SCA schemes are not at all prescriptive regarding the types of activities and assessment metrics that are required. For example, the Canadian Roundtable for Sustainable Beef’s (CRSB) Sustainable Beef Production Standard [24] simply states that the highest level of credential is achieved when the “Operation assesses the success of practices that are supporting carbon sequestration or minimizing emissions”. No indication of the level of detail for the assessment is suggested, although their documentation also suggests that for production systems deemed to be high-risk, a full on-site audit and then three full record assessments are required within 5 years for certification. There is a lot of interconnectedness among the schemes, as has been identified in the Supplementary Material. For example, the FAO SAFA guidelines [11] refer to an approach based on Environmental Life Cycle Analysis (LCA) within an ISO standard framework. However, this may require ISO standard frameworks to be available or adapted for a wide range of production conditions and sensitive to quantify change in an environmental credential through LCA analyses.

The quality of pasture has been identified as an important factor in total emissions, whereas pasture quantity and potential constraint to intake have not. This may be because there are more direct methods to estimate intake based on LW and LWG (e.g., SB-GAF, [128]). In the case of enteric emissions from feedlot cattle, feed intake (kg dry matter head⁻¹ day⁻¹) is estimated using the Intergovernmental Panel on Climate Change’s (IPCC) [6] simplified tier 2 method, based on LW and dietary net energy concentration. Methane yield is then calculated using [129].

Enteric CH₄ emissions and land use change (deforestation) make up most emissions within livestock systems. Although the quantification of emissions from these is not necessarily explicit in the schemes, prioritizing their measurement may be important [9]. However, livestock management projects addressing enteric emissions have not been well taken up by industry (see Section 6).

4. Emissions Intensity

Emissions intensity is the level of GHG emissions per unit of product, typically kilograms of live weight or carcass weight produced in the case of beef production. Emissions intensity can vary widely between production systems due to both the management of inputs and the efficiency of production from the herd and general environmental and climatic factors. Emissions intensity values have been reported by Browne et al. [130] for benchmarked average and top producers for a range of livestock enterprises, including cow calves and steers in temperate systems. As might be expected, the emissions intensity of cow-calf production was about 3.5 times greater than that of steer production (22.4 vs. 6.7 t CO_2-e t⁻¹ product for benchmark average [130]). Substantive differences in GHG emissions intensity exist in different types of production systems, for example, between arid, humid and temperate climatic zones [121]. Some of the assumptions used in FAO’s GLEAM model [131] (e.g., excluding sandy soils) may have increased uncertainty in the estimates of emissions intensity within production zones [131]. The level of applied and deposited manure is the biggest factor varying between the three production zones, which reflects the significance of nitrous oxide GHG emissions. Enteric CH₄ accounted for about 50% of GHG emissions per unit product in all three systems.

Enteric CH₄ is the largest source of emission intensity in all systems; however, it is highest in the arid and humid zones of both grazing and mixed farming systems, where feed, for the most part, is of lower quality. As CH₄ emissions are largely driven by the livestock enterprise and pasture management, biophysical models are useful to investigate finer-scale changes to livestock enterprise scenarios [132]. Changes to reproduction and diet quality substantially change the amount and intensity of emissions and the level of production, so they are strong drivers of improvement in emissions intensity.

The SB-GAF [25], developed by the University of Melbourne, is intended for use in sheep and beef cattle grazing businesses, particularly enabling a baseline analysis to compare the effects of other scenarios such as changes to land use, livestock enterprise or sequestration opportunities. SB-GAF is used to compare scenarios with different emissions intensities [25].

The ERF Beef Cattle Herd Management Calculator [18] must be used to estimate the total emissions and emissions intensity of ERF-registered projects. It appears to be a simplified version of SB-GAF, particularly in the data structure for the input of animal classes and numbers, average LW, and average LWG on a seasonal basis. It was designed primarily to assist with requirements for reporting to the timeframes of the Beef Herd Management method for the reference years and crediting years. It appears to be a simpler tool with hidden and protected formulas, giving little opportunity to refine data inputs or to clearly understand the calculations. All outputs (enteric CH₄, N₂O) are converted into t CO_2-e y⁻¹ and LWG as t y⁻¹.

The Australian Government Clean Energy Regulator [41] oversees the ERF [28], which provides a mechanism to register projects that can earn Australian Carbon Credit Units (ACCUs) for emissions avoidance or carbon storage. Some ERF methods also consider emissions intensity, with producers receiving ACCUs for activities that reduce emissions intensity. Further details of the ERF are outlined in Section 6.

5. Carbon Sequestration

As land custodians and managers, farmers are uniquely placed to implement farming practice changes that will increase the storage or minimize the losses of carbon within agricultural landscapes. Carbon storage is a product of the carbon estimation area available for sequestration and the carbon sequestration rate of organic soil and vegetation carbon. Perennial plants, particularly shrubs and trees, are the primary mechanism approved by the ERF to sequester carbon within extensive livestock systems [133,134,135]. Similarly, the protection of remnant vegetation or allowing regeneration of native flora in some areas of the farm will result in carbon storage. Other practices that can result in carbon sequestration include conservation tillage, the retention of crop residues, the reduced use of fallowing, the conversion from annual to perennial crops or pasture, improved grazing management, and sowing forage species that produce more biomass [136,137]. These mechanisms tend to increase the storage of soil organic carbon (SOC); however, there is still substantial uncertainty around the achievable rates of soil carbon sequestration and its permanence [137]. Schwenke et al. [138] concluded that only a complete change in land use from cropping to perennial-grass-based pastures has been clearly demonstrated to significantly restore total organic carbon in degraded cropping soils, at least on heavy-textured clay soils [139,140,141]. However, Meier et al. [142] argue that it is crucial to consider all GHG emissions when evaluating the abatement potential of different farming systems and practices and that these practices need to be tailored to the climate, crops, soils, and management at locations. In their simulation study across three contrasting environments in Australia, net emissions from stocked permanent pastures were not always less than those from cropping systems. This was because enteric CH₄ emissions from livestock were not consistently offset by increased SOC under permanent pastures relative to the cropped systems. A key influence upon carbon inputs to soils in two of the case studies reported was that low summer rainfall limits pasture growth in the livestock scenarios to a similar period as that in which crops are grown in the cropping scenarios. And in these predominantly cropping environments, where a key role of the pasture phase is as a disease break in cropping rotations, pastures generally receive little or no fertilizer, limiting pasture growth and carbon sequestration potential.

The sequestration and storage of SOC should not be at the expense of system health and productivity. The capacity to maintain or improve enterprise production will need to be considered. This applies not only at the farm scale but also at the regional and national scales. One of the purposes of schemes and standards is to facilitate external investment into agricultural land to generate carbon credits for trading to offset emissions from other industries. A high risk of non-agricultural investment in carbon sequestration programs is that these objectives are not the priority and may result in locking up the most productive land as the most effective way to obtain the credits [143,144]. Increasing SOC provides a better opportunity for positive trade-offs between production and carbon sequestration than forestry. However, the potential for the climate to limit the accumulation of SOC should be recognized [145,146].

Table 2. Summary of measures used by SCA schemes to determine carbon stocks and fluxes and sequestration for grass-fed beef production.

Metric	Method or Data Source	Method Specification	References
Soil management
Soil organic carbon (SOC)	Soil sampling	NATA accredited agents Sampling date Sampling depth (cm) Method of analysis Partition to C pools Soil OM added (kg ha-1)	[14,16,21,23,44,45,46,50]
Ground cover	Field survey GIS maps	Remote Sensing data sources Fractional Cover (PV/NPV/Bare %) Forest/woody/bare (%)	[16,21,26,28,32,33,44]
Vegetation management *
Total biomass (kg/ha)	Field survey	Volume of harvested wood (m3) Volume of woody detritus left on-site (m3)	[16,21,27,43,46]
Land use change
Land types and species	Field survey Farm records GIS maps	Land type (forest, woodland, cleared) Tree species Area of land (ha) Area of trees (ha) Age of trees (y) Year of Land Use Change (y)	[14,25,27,28,29,33,46]
% Land allocated to beef	Farm records	SB-GAF, F-GAF	[25,29]
Tilling practices	Farm records GIS maps	Types of tilling practice Year of practice change (y) Cropland Area change (ha)	[11,14,22,27]

* This refers to native vegetation and environmental plantings. Abbreviations: GIS, geographic information system; OM, organic matter; NPV, non-photosynthetic vegetation; PV, photosynthetic vegetation.

presents the various metrics and measurements associated with determining carbon storage and sequestration associated with grass-fed beef production within SCA schemes and outlines the specification of methods and any associated references that provide scientific support and verification.

6. Climate Credentials

A target of carbon neutrality by 2030 has been set by the Australian red meat industry [15]. As an industry target, this does not require every enterprise to achieve a carbon-neutral position. But overall, the industry in Australia has opportunities to both reduce enteric CH₄ emissions through technology development and store carbon over the vast land areas on which the industry operates. This combination of activities is the basis of achieving net zero industry emissions or carbon-neutral farming. Carbon-neutral farming (based on CO₂-e) is the point at which the total emissions of a beef enterprise are equivalent to the amount of CO₂-e stored. This is consistent with the aim of FAO’s SAFA guidelines [11] that set out an objective for an enterprise’s GHG emissions to be contained [11]. For this review, it includes on-farm and processor components of the supply chain. Recent research indicates that carbon neutrality in beef production is possible in some situations but will require clear pathways for producers to adopt persistent options for emissions reduction and vegetation management [147]. These activities need to be underpinned by reporting and certification [122], supported by quantitative methods, measures, and metrics. Effectively, the options and systems discussed in Section 2, Section 3 and Section 4 will require a suitable accounting framework that is verified on an ongoing basis through appropriate credentialing or audit processes.

Over the past several decades, various GHG and carbon accounting systems have been developed to quantify effects on the balance of atmospheric GHGs and associated global warming. Leading examples of this are OverseerFM [59] (New Zealand), Cool Farm Alliance [58] (United Kingdom), GHG Protocol Agricultural Guidance [14] (Global) and GHG Accounting Frameworks for Australian Primary Industries [148] (Australia).

To achieve carbon-neutral status for business activities, the following steps have been suggested (Climate Active [39]):

• Define the emissions boundary;
• Calculate total emissions;
• Develop and implement an emission-reduction strategy based on an emissions inventory or life cycle assessment, generally by an expert consultant;
• Purchase offsets to cover any emissions that are not able to be reduced or inset within the business.

Meeting Australia’s 2030 target of net zero emissions will require a combination of emissions reduction and increased carbon storage across many sectors of the economy, particularly the energy sector, which produces about two-thirds of GHG emissions [40]. Agricultural systems, currently responsible for 15.8% of GHG emissions in Australia, are also considered the go-to option for carbon sequestration and emission-avoidance activities, given their role in land stewardship.

The ERF was established in 2014 by the Australian Government to define methods and practices that are eligible to generate Australian Carbon Credit Units (ACCUs) [41]. Several SCA schemes refer to ERF compliance to verify their methods to reduce emissions or sequester carbon and thereby claim credits. The list of approved methods for the land sector are listed in

Table 3. ERF methods relevant to grass-fed beef and their Legislative Determination ID.

Agricultural Method	Determination ID
Reduced enteric CH4 entering the atmosphere
2. Beef cattle herd management method The beef herd method provides incentives for managers of grazing cattle herds to introduce one or more new or materially different activities that reduce the emissions intensity of their herd(s).	F2017C00466
3. Reducing greenhouse gas emissions by feeding nitrates to beef cattle	F2015C00580
Carbon sequestration (soil)
5. Estimating sequestration of carbon in soil using default values (model-based soil carbon)	F2018C00311
6. Estimation of soil organic carbon sequestration using measurement and models method	F2021L01696
Carbon sequestration (vegetation)
7. Avoided clearing of native regrowth	F2018C00127
8. Designated Verified Carbon Standard projects method	F2015L00320
9. Human-induced regeneration of a permanent even-aged native forest 1.1 method	F2018C00125
10. Native forest from managed regrowth	F2018C00119
11. Measurement-based methods for new farm forestry plantations	F2015C00577
12. Plantation forestry (2022)	F2022L00047
13. Reforestation and afforestation 2.0 method	F2015L00682
14. Reforestation by Environmental or Mallee Plantings–FullCAM	F2018C00118
18. Tidal restoration of blue carbon ecosystems method	F2022L00046
Savanna fire management
17b. Savanna fire management 2018—sequestration and emissions avoidance	F2018L00562
17a. Savanna fire management 2018—emissions avoidance	F2015L00344
Methods in development
The Integrated Farm Management method. Aims to increase the carbon pools and activities for which individual projects may receive credits, while reducing the administrative costs associated with registering, reporting, and auditing on multiple projects.
Revoked methods in 2023 *
Avoided deforestation V1.1	F2015L00347
Human-Induced regeneration of a permanent even-aged native forest V1.0	F2018C00125
Quantifying carbon sequestration by permanent environmental plantings of native species using the CFI reforestation modelling tool
Quantifying carbon sequestration by permanent mallee plantings using the reforestation modelling tool
Reforestation and afforestation (1.0, 1.1 and 1.2)	F2013L01210
Reduction of greenhouse gas emissions through early dry season savanna burning (1.0 and 1.1)	F2013L01165
Emissions Abatement through Savanna Fire Management 2015	F2015L00344
Sequestering carbon in soils in grazing systems	F2018C00120
Measurement of soil carbon sequestration in agricultural systems	F2018L00089
Plantation forestry (2017)	F2020C00072

* Projects that were registered under these carbon-crediting methods may continue. No new projects may be registered under them.

as well as some recently revoked methods that fall under the categories of agricultural, savanna fire management and vegetation [149].

For grass-fed beef businesses, the options for ERF agricultural methods that target enteric emissions through livestock management appear limited relative to the number of vegetation methods (Table 3). The choice is between methods that measure or estimate SOC sequestration through pasture and crop management (conversion, retention and intensification) (methods 5 and 6, Table 3) or the Beef Herd Management (BHM) method (method 2, Table 3, [18]), which aims to reduce emissions intensity per kg of LW produced. In tropical northern Australia’s rangelands, savanna fire management and reduced GHG through feeding nitrates to cattle are additional options. The SOC sequestration methods have longer-term permanence obligations and a crediting period (≥25 years). Potential sequestration rates are variable and very dependent on the environment and climate conditions and carry the risk of reversal. Moreover, there will be ongoing costly annual soil sampling to establish trends in SOC sequestration.

The BHM method has a shorter crediting period of 7 years. The herd is the project boundary; i.e., it is managed as a discrete set of animals over time, but adding more herds to the project is possible. The reporting of data requires the frequent weighing of all classes across the herd inventory, including traded stock. The herd will have historical emissions intensity data on which to base the baseline for the herd. The BHM method reduces the emissions intensity of beef cattle production by increasing the ratio of weight to age of the herd, reducing the average age of the herd, reducing the proportion of unproductive animals in the herd, changing the ratio of livestock classes within the herd to increase total annual live weight gain of the herd, and reducing the time for young cattle before they reach market specifications. In addition to enhanced herd management, improved pasture and forage management, in production, allocation and utilization, will be essential to achieve the improved LWG and rates to reduce emissions intensity. While the improved pasture and crop management are likely to also contribute to SOC accumulation, there is no provision in the method to account for this as part of the net business emissions.

An inspection of the almost 1480 Land Sector projects in the ERF project register [150] (Accessed 14 June 2023) lists 870 Vegetation, 509 Agriculture and 98 Savanna Burning projects. Similarly, projects listed in the Climate Active website show a higher proportion of “Vegetation” rather than “Agricultural” methods. For most of these “Vegetation” projects, carbon sequestration is achieved by allocating greater proportions of the farm business to native forest regeneration, environmental reforestation, or plantation forestry, or through emission avoidance, leading to concerns about unintended consequences if incentivizing carbon sequestration.

Of the 509 agriculture methods, 470 projects targeted the measurement or estimation of SOC sequestration, and only 1 has been issued a total of 1904 ACCUs. Fourteen projects were registered under the Beef Herd Management method [18], where three of these projects received 874,225 ACCUs valued at AUD 14.86 M based on ERF Auction results in March 2023. The remaining 25 projects relate to the management of CH₄ and effluent from intensive production (piggery and dairy ponds), and they received a total of 1,108,373 ACCUs valued at AUD 18.84 M based on the latest ERF Auction results in March 2023 [28].

Although Australian agriculture in 2014 had promised 15.2 Mt of CO₂-e abatement, by April 2022, it had delivered only 1.1 Mt [151]. The current methods are restrictive due to the single implementation of eligible activities, which may be limiting uptake. A new method, “Integrated Farm Management” (IFM), is under development and will allow separate land-based activities to be combined or “stacked” on the same property or aggregated properties. The IFM method aims to increase the carbon pools and activities for which individual projects may receive credits while reducing the administrative costs associated with registering, reporting and auditing on multiple projects [41]. It could potentially allow for the accounting of SOC sequestration associated with crop-pasture management as part of the BHM method. An approved method of suppressing enteric CH₄ emissions (e.g., red algae, [152]) is not yet available, and algal production needs to be scaled up commercially and proven for grazing animals. The main constraints on soil carbon sequestration (SCS) are the unreliability of Australian rainfall, the high cost of project management relative to the value of an ACCU, and the opportunity cost of maintaining approved land management for at least 25 years [151,153].

Speculation about the unintended consequences of some of the vegetation method choices includes the potential reduced availability or the increased price of productive agricultural land [143,144]. This will increase the challenge of achieving Australia’s agricultural production and economic targets (AUD 100 billion by 2030, [154]) and will have an adverse effect on global food security. So strongly incentivizing carbon storage on agricultural land needs to be viewed with some caution, particularly if climate credits are traded to markets outside the agricultural industry/red meat sector. Despite this, it is unlikely that global climate targets will be met for the foreseeable future unless the agriculture sector is able to create strong net negative emissions [155]. In view of emerging economic incentives for climate credentials, primary producers are likely to continue to weigh up their options based on the risks and rewards associated with their business. The Clean Energy Regulator [41] warns potential investors in vegetation or sequestration projects to be wary of expected “Return On Investments“ from sequestration projects due to misleading claims [156], particularly about unrealistic minimum returns on investment or returns that are government-guaranteed.

7. Biodiversity Credentials

Producers are responsible for the short- and long-term management of all vegetation in extensive beef systems, with flow-on effects on ecosystem biodiversity [157]. Land use change is a key driver of the decline in biodiversity globally, and the land use change associated with agriculture poses a persistent threat to biodiversity [5,158]. As extensive beef systems vary widely across Australia due to differences in climate (e.g., temperate, tropical, and semi-arid) and management practices, the effects of livestock production on biodiversity also vary widely [159]. In some instances, well-managed pasture and rangeland livestock systems may benefit biodiversity outcomes [159,160]. However, more commonly, there are biodiversity benefits from reducing livestock grazing [161]. In relation to the potential displacement of cropping via beef production, Ridoutt and Navarro Garcia [162] show that Australian beef has a low footprint for (a) the cropland occupation, (b) the cropland scarcity footprint, (c) the cropland malnutrition footprint and d) the cropland biodiversity footprint. Management factors that affect biodiversity in grazing systems have been reviewed by Rook et al. [163]. Science-based methods for the assessment of biodiversity in permanent pastures in Australia have been developed, for example, the Accounting for Nature^® framework [16]. Preserving biodiversity requires strategies to avoid land use conversion to agriculture, maintain and improve habitat conditions, and remove invasive plant and animal species that threaten biodiversity [164].

In this review, the primary focus was on methods used to quantitatively assess biodiversity, measured against a baseline of pre-European land conditions or how biodiversity is changing over time. Typically, it is not possible to achieve accurate accounting of species abundance and population status (susceptibility to extinction) without significant investment of resources, so methods for habitat condition assessment are widely used as indicators of biodiversity [17,165]. GHG and biodiversity are considered jointly in about 20% of the SCA schemes reviewed. However, the measurement of biodiversity and habitat condition should be considered separately from the measurement of carbon storage in grazing enterprises, as these two ecosystem services have differing characteristics. For example, remnant vegetation that has been heavily grazed may retain biomass and carbon due to the persistence of trees, woody shrubs and less palatable grasses but may have a reduced capacity to support biodiversity [161,166]. Also, carbon projects designed to increase vegetation biomass do not necessarily provide biodiversity benefits, where those projects rely on carbon production from plant species assemblages that lack suitable diversity, do not provide the necessary habitat complexity or are unsuited to local biodiversity requirements [167,168]. Reside et al. [167] argue that opportunities for carbon storage should have robust assessments for biodiversity conservation and consider additional incentives for improved biodiversity outcomes. This may help limit the prioritization of projects where carbon storage is maximized at the expense of other ecosystem services and help to achieve multiple benefits—carbon and biodiversity—from a given piece of land.

The purpose of

Table 4. Ecosystem condition indicators for biodiversity and the associated methods and data that were available from SCA scheme documentation.

Metric	Method or Data Source	Method Specification	References
Habitat assessment
Conservation value	Assessment using the High Conservation Value (HCV) framework.	An HCV is a biological, ecological, social, or cultural value of outstanding significance of critical importance. Six categories of HCVs, including species diversity, landscape-level ecosystems and mosaics, ecosystems and habitats, ecosystem services, community needs and cultural values	[17,53]
Farm biodiversity benchmark	Field survey Farm records	Assessment of the condition of the farm’s “native vegetation” for biodiversity, relative to a “regional condition benchmark”. A 0–1 scale from degraded to natural condition. Three levels of certification (Provisional, Green and Gold). Farm results were compared against a national minimum of 0.1 and the applicable regional condition benchmark. Engagement with a specified management plan.	[16,17,35,52]
Habitat condition	Remote sensed biotic data, e.g., NDVI Expert site assessment	Observed tree cover compared with 90th percentile cover at 100 km2 tiles. Habitat condition at project sites compared with reference sites. A scale (0–1) for degraded to natural condition.	[17,52,53,56,169]
Land types and species	Property maps	Species diversity and abundance Property Map of Assessable Vegetation (PMAV)	[11,14,17,31,35,53,56,170]
	Farm Records and GIS	Property extent, Area of land (accounting area)	[14,31,35]
Land set aside for conservation		Quality and quantity of natural vegetation in the project area	[11,15,26,32,51,53]
a Extent	Desktop survey GIS and vegetation map. Remote sensing.	Benchmark of 100% taken from surrounding reserves	[16,35,54,55,56,171]
b Configuration	Desktop survey	GIS and a current vegetation map and on-ground/aerial photography verification. Benchmark of 100% as the pre-1750 extent of all vegetation types 1–5 km from each sample site.	[16,35,54,55]
c Composition	Desktop survey Field survey Biodiversity models Remote sensing and analytics Biodiversity questionnaire Local knowledge	Standing trees (DBH >100 mm) Fallen timber >100 mm diameter Native tree canopy height, canopy health score, canopy cover, density, species count for tree canopy and shrub layer species Native shrub, herbaceous cover Non-native shrub, tree, herbaceous cover Organic litter ground cover, cryptogam, forage/grass, and woody cover Presence of weeds, pasture composition, pasture quality Erosion	[16,17,31,36,52,53,54,55,56]
Ground Cover (See also Table 2)	Field survey GIS maps	Groundcover (% total groundcover) Persistent green cover fraction Recurrent green cover fraction Litter cover fraction Bare ground fraction	[16,17,31,32,33,36,55,62,172,173]
Habitat connectedness	Field survey GIS maps	Patch- or grid-based, neighborhood- and system-level analysis	[17,35,52,56]
Species status	Direct observation Habitat-based approach	Extinction risk	[56]
Species stocks	Field survey	Opening and closing entry for accounting period	[53,56]
Threats to biodiversity	Biodiversity questions		[52,53]
Soil condition	Field and lab measurement of topsoil samples collected Field survey	Soil acidification (pH-CaCl2) Soil organic carbon (% dry wt. basis) Soil salinity (EC, dS m−1) Extractable phosphorus (Olsen P, mg kg−1)	[16,31,62,174]
Catchment health and water quality	Monitoring riparian areas and wetlands Identifying potential contaminants		[24]
Management measures
Business plan	Farm records	Biodiversity management plan (BMP)	[31,35,51]
Revegetation	Farm records Revegetation modelling	Habitat condition predicted using logistic model Potential habitat condition	[52]
Certification	Documents	BMP Certified	[31]
Grazing management	Farm records	Rotational grazing Limit grazing pressure	[31,36]
Pasture management	Farm records	Monitoring/improving species composition	[31]
Weed control	Farm records	Regular interventions	[31]
Feral animal control	Farm records	Regular interventions	[31]
Water/runoff quality	Farm records	Monitoring EC, pH, turbidity downstream Cattle nutrient management	[31]
Drought management	Farm records Sales records	Destocking, early weaning	[31,36]

^a Extent: The proportion of remnant vegetation remaining within the accounting area compared to the extent in the year 1750. ^b Configuration: The configuration of native vegetation relates to its connectivity, context and patch size within the local landscape (i.e., in the vicinity of the sample site). ^c Composition: The composition of native vegetation relates to its structure and the assemblage of species. Abbreviations: PMAV, Property Maps of Assessable Vegetation. BMP, biodiversity management plan. DBH, diameter at breast height. EC, electrical conductivity. ds m⁻¹, deciSiemens per meter. GIS, geographic information system. NRM, natural resource management.

was to identify indicators, methods and data sources associated with biodiversity assessment that are used within SCA schemes and relevant to grass-fed beef production. It should be noted that in many cases, these details were not readily available, so the table presents a limited overview based on the information that was publicly available in the SCA schemes reviewed.

In Australia, biodiversity assessment for the beef industry would apply across a vast area and a wide range of circumstances, so it will need a broad range of approaches (Table 4). Assessment methods and schemes must be both suitably rigorous (to ensure they meaningfully measure biodiversity outcomes) and simple enough for end users to understand and implement [175]. Striking this balance is essential for credentialing schemes to be robust and trusted. This principle has been noted in the development of some of the schemes; for example, the “rules of thumb” applied within the Social and Biodiversity Impact Assessment [175] are that biodiversity objectives should be (1) few in number and (2) easy to assess and quantify using practical indicators.

A common theme of biodiversity assessment is the benchmarking of areas of agricultural land use (e.g., at the individual farm scale) against reference sites of undisturbed or natural vegetation. To meaningfully assess the habitat condition of a given location, an extensive collection of field survey data that can be used to calibrate scalable models is required. To achieve this, the National Reference Library of Expert Site Condition Assessments [176] piloted a novel, national approach to collecting expert site condition assessments and calibrating participant expertise within a common conceptual framework.

8. Key Assessment Approaches and Recommendations

8.1. Design of Credentialing Methods

The development and implementation of sustainability schemes for beef production are still in their early stages internationally and will need focused attention to meet internationally agreed targets given that there are less than seven years remaining to meet the goals of the United Nations 2030 Agenda for Sustainable Development [177]. To ensure consumer acceptance of beef products and meet sustainable procurement standards, it is imperative to demonstrate that underpinning sustainability schemes are credible and will achieve stated sustainability objectives [178,179]. This will require transparent certification processes, robust monitoring and reporting mechanisms, and adherence to recognized standards and benchmarks. However, beef producers need to be confident that providing data to support credentials will benefit their business, or they may be reluctant to engage [180]. The credibility and value proposition of these schemes need to be demonstrated, so that both producers will engage and consumers can make informed choices and support sustainable beef production. While certain regions, notably Europe, have made significant progress in the adoption of SCA schemes using subsidies (i.e., the consumer pays indirectly for the adoption of these practices), there is a need to recognize that this approach may not be applicable to other production systems and jurisdictions. Localized concerns, such as land use, water scarcity, biodiversity loss and capacity, practicality and the cost of collecting measurements and data, may require tailored approaches, and this should be considered during the design and implementation of these schemes.

Design criteria provide a structured approach to developing and refining the framework and implementation strategies of credentials. They serve as guiding principles that help address specific challenges and maximize the potential benefits of the credentialing system. In the case of ISO 14064-1:2018 [181], the six principles of relevance, completeness, consistency, accuracy, transparency and conservativeness were applied [21].

In the development of recommendations and methods to attain climate and biodiversity credentials for grass-fed beef, we have developed and applied the following design criteria.

Flexibility: Recognizing the dynamic nature of markets and policies, it is important to establish a credentialing system that can adapt to evolving circumstances. The emergence of new information through digital technologies and other sources necessitates a flexible framework that can incorporate and integrate these updates effectively.

Clear outcome: The objective is to motivate improved environmental management by providing a verifiable means for beef producers to communicate current and changing practices within their businesses. This can be achieved with a suitable assessment framework for emissions mitigation and lower emissions intensity and enable improvements in habitat conditions and biodiversity. Ultimately, a credential system should enable working toward the beef industry’s carbon neutrality and biodiversity goals and be aligned with international targets such as the UN Sustainable Development Goals [177]. This focus on clear outcomes provides a foundation for improved social acceptance and access to markets, facilitating the transition toward sustainable practices.

Performance-based approach: Acknowledging the diversity of contexts and approaches within the beef production sector, the credentialing system should not be overly prescriptive. Instead, it should accommodate a wide range of viable and accepted strategies for enhancing climate and biodiversity credentials and base performance on objectively measured outcomes. This flexibility allows for tailored approaches that consider the specific circumstances of different producers.

Recognition and reward for positive change: It should be ensured that the implementation of practices targeting positive changes made by beef producers are duly acknowledged by the stakeholder base and that, in time, producers may be rewarded by the market through value-added differentiation. By incentivizing and recognizing efforts to improve climate and biodiversity credentials, the industry can encourage continuous improvement and wider participation among producers.

Inform the development of digital credentialing: The findings and recommendations from this review have contributed to the development of a digital credentialing platform. The purpose of the platform is to serve as digital infrastructure for data curation to support the assessment, verification and monitoring of sustainability credentials, and incorporating insights from this research ensures its alignment with the identified design criteria.

Focus on scalable methods: To promote widespread adoption of climate and biodiversity credentials, the recommended methods should be scalable. A capacity to apply quantitative metrics to support credentials using universally accessible data sources, such as farm records and remotely sensed data, will allow the credential methods to be applicable across large-scale industries such as the Australian beef industry. It is anticipated that this will reduce the cost and time required for implementation and drive a focus on quantitative metrics with defined uncertainty estimates that are also amenable to benchmarking.

Science-based measures and trusted data sources: The development of climate and biodiversity credentials relies on using scientifically sound measures and metrics. This necessitates the utilization of trusted data sources that provide accurate and reliable information for assessing environmental performance. By employing scientifically verified methodologies and credible data, the integrity and credibility of the credentialing system are defensible.

8.2. Recommendations for Credentials

The uptake of credentials by beef producers is influenced by factors related to their business and the design and implementation of the credentialing system. In applying credentialing metrics, the schemes seek to find a balance between accurate and verifiable measures and the ease and expense of implementation. A system that is too onerous or costly would discourage engagement from producers and other stakeholders. In Australia, most schemes rely on voluntary participation and tend to have tiered credentialing to cater for differences in the desire and capacity of producers to be involved. However, producers may be encouraged or incentivized by customers, policies or market access.

Confidence in the value of achieving credentials, the ease of implementation and a strong value proposition as an incentive were all significant factors for the expansion of credentials in grass-fed beef production [182]. As Glasbergen [182] points out, those responsible for developing credentialing frameworks may have limited knowledge of the lived experience of primary producers. Further, some participants fear that voluntary schemes will eventually become compulsory for market access [182]. Therefore, designing credentialing incentives that do not become eroded over time is a key factor for their adoption by producers.

The recommendations proposed by this review consider the evolving climate and biodiversity credential markets, anticipating advancements in technology, increased incentives, and the use of tiered credentials to facilitate industry participation. By examining the evolving landscape of credential markets, emerging technologies and growing incentives, this review provides recommendations to enable industry-wide participation and continuous improvement. The appropriate verification of schemes and their methods is another component to be considered in a credentialing framework, with governance and scientific validity being key to a functioning credentialing mechanism.

Recommendations for the development of Australian beef industry credentials were based on our review of existing SCA schemes, relevant literature and expert consultation through research and industry advisory panels. The eight recommendations for credentials are outlined in Figure 1 and detailed in the subsequent section.

8.2.1. Recommendation 1: Climate and Biodiversity Credentials Jointly Prioritized

GHG emissions and biodiversity were the priority areas identified for credentialing for the grass-fed beef industry. Climate and biodiversity were considered jointly in many of the SCA schemes reviewed. An overall benefit–cost evaluation of planned activities would need to consider joint impacts on climate, biodiversity and productivity. In some situations, improved biodiversity may enhance profitability, but in others, it may have a neutral or negative impact on profitability. For example, in cases where native herbivores build up in number, they can consume large quantities of forage intended for livestock and may contribute to problems of overgrazing [183] or damage to crops, incurring financial losses.

Several key metrics need to be carefully selected for the verification of credentials and benchmarking. Ideally, these credentials would follow a defined protocol based on information specific to the credential domain. For biodiversity credentials, the use of habitat condition assessment is a generally accepted proxy for biodiversity [184]. According to the Habitat Condition Assessment System for Australia (HCAS), the definition of “Habitat Condition” is “the capacity of an area to provide the structures and functions necessary for the persistence of all species naturally expected to occur in that area if it were in a reference state” [17,185]. For climate, GHG accounting methods are required, including metrics such as emissions intensity, net/total emissions and carbon stores in the soil and vegetation. Producers will have varying experience, with production-recording and account-keeping procedures that are needed to inform climate and biodiversity credentials. A tiered approach will provide entry-level credentialing across the Australian beef industry that becomes more sophisticated as producers gain entry to the higher tiers. There will be a need to ensure flexibility and updatability in measurement methods and analytical approaches from the initial starting position, for example, applying a framework where several data sources can be linked with a parent metric when calculating a benchmarking value for credentialing.

8.2.2. Recommendation 2: Building Engagement through Tiers

The use of tiered levels of engagement in sustainability practices was applied to encourage entry-level participation in other sectors of the agricultural industry [186]. A tiered approach was also a feature in SCA schemes reviewed in this paper (e.g., [16], Australian Farm Biodiversity Certification, [24], FAO low carbon livestock). Three tiers of credentialing were proposed, as illustrated in Figure 2: credentials based on training (Tier 1), implementation (Tier 2) and benchmarking (Tier 3), which captures the intent for carbon and biodiversity assessments within an enterprise from a baseline year and between comparable enterprises with similar land types within agroecological regions. In addition are appropriate training material (Tier 1), whole-farm remotely sensed assessment metrics and opportunities for improvement based on a defined SMART (Specific, Measurable, Achievable, Relevant and Time-Bound) management plan (Tier 2) and benchmarking to allow tracking of progress for climate and biodiversity (Tier 3).

The benchmarking of livestock production efficiency between businesses and industries may be achieved provided the appropriate metrics are selected [130]. Benchmarking has been widely used to compare GHG emissions for different livestock systems in Europe [187,188,189]. Benchmarking should be conducted across a sufficient timeframe to account for variability in seasonal and inter-annual conditions that may affect GHG emissions, carbon sequestration and biodiversity indicators. Interactive tools for GHG assessment, such as FarmPrint [22], may provide options for user-friendly assessment for businesses. Benchmarking based on published values may serve as a starting point for some credentials’ measures (e.g., emissions intensity, [130]). Beef enterprises may initially use standardized or normalized values for the region (e.g., a Gross Margin template, or Australian Bureau of Statistics data) for benchmarking but could use comparison with aggregated data from neighboring farms within regions where credentials have been achieved. This could be linked with the greater incentives that will be needed to encourage producers to advance between tiers.

Digital livestock management systems aim to improve efficiency and productivity. They were seen as a key tool to enable improvements in the sustainability of livestock production [190]. If they are to be used in credentialing, they need to report on the defined metrics and indicators. Such digital credentialing systems need to be designed with entry-level users in mind, with usable input and interpretable output values that can be adapted to a range of grass-fed beef production systems. They should also enable progression to support the participation of higher-ambition businesses and drive continuous sustainability improvement. As outlined previously, we suggest a tiered approach to credentialing to allow a broader group of livestock businesses to engage. A summary description of the three climate and biodiversity tiers proposed in Figure 2 is outlined in

Table 5. Climate and biodiversity criteria associated with the three tiers of credentials proposed.

Tier	Level	Criteria
Climate
Tier 1	Aware (Learn and plan)	Trained in basics of on-farm emissions accounting for beef production. Familiar with credentials platform and basic data inputs. Have a basic management plan for own business, with change options identified.
Tier 2	Actioned (Measure and manage)	Conducted a whole of business assessment of GHG emissions/emissions intensity and carbon stocks and potential sequestration. Implemented changes toward improving net emissions/emissions intensity.
Tier 3	Committed (Monitor and improve)	Net GHG emissions and emissions intensity benchmarked internally across years and with comparable similarly sized and operated businesses within single years. Trend for continuous improvement or top 25% relative to benchmark for net GHG emissions/intensity over the previous 5 years.
Biodiversity
Tier 1	Aware (Learn and plan)	Trained in basics of on-farm habitat condition (biodiversity) assessment for beef production. Familiar with credentials platform and basic data inputs. Have a basic management plan for one’s own business, with change options identified.
Tier 2	Actioned (Measure and manage)	Implemented an ongoing system for assessment of habitat condition (biodiversity). Implemented changes toward improving habitat condition or biodiversity.
Tier 3	Committed (Monitor and improve)	Habitat condition (biodiversity) benchmarked with comparable businesses with the same agroecological attributes/limitations. Trend for continuous improvement or top 25% relative to benchmark in habitat condition or biodiversity over the previous 5 years

. A consistent approach was taken for the design of the three tiers for climate and biodiversity. While ongoing improvement and progression through the tiers are encouraged for new entrants to the credentialing system, a mechanism to reward businesses that have demonstrated existing high levels of climate and biodiversity credentials was included. This is achieved through Tier 3, which provides both the scope for demonstrating ongoing improvement and the option to achieve the credential by being in the top 25% relative to the benchmark. As the overall level of the beef industry’s climate and biodiversity credentials improve, by definition, the top 25% of producers would need to continue to improve to meet this target. One of the contentions with encouraging more sustainable practices is additivity [191], which can disadvantage good land managers and even encourage poor management practices while a baseline for improvement is set.

8.2.3. Recommendation 3: Fewer Priority Focus Areas

Due to the complexity of GHG and biodiversity accounts, there are many activities that might be undertaken to improve credentials. It is important to balance positive interventions that are easy to implement and not detrimental to profitability with interventions that can achieve substantive emissions reduction and biodiversity benefits (e.g., beef herd management, enteric CH₄-reducing supplements and habitat connectivity). The implementation of synergistic interventions to accelerate progress while also improving farm performance will perhaps be more likely to be adopted (e.g., establishing environmental plantings to improve habitat connectivity by selecting topography that will also improve shade/shelter or reverse the impacts of salinity). Small positive changes may improve the adoption of credentialing but might also be diverted toward enabling “symbolic” rather than “substantive” corporate social actions [192]. A focus on fewer priority areas for credentialing will likely lead to a less confusing operating environment and produce improved sustainability outcomes.

8.2.4. Recommendation 4: Provide Clarity and Certainty in Implementing Credentialing Pathways

A centrally coordinated platform, with defined tiers and methods, will provide the industry with well-understood requirements for achieving environmental credentials while engaged in grass-fed beef production. The environmental performance of agricultural industries is an expectation in society, and demonstrating this will help to ensure social licence domestically and ongoing access to international markets. The challenges and limitations of SCA schemes can impact their adoption by creating barriers to entry, increasing complexity, and reducing relevance and perceived value. Currently, multiple schemes with differing credentialing rules and methods of implementation (e.g., changes in the interpretation of emissions factors) undermine the value proposition of credentialing for beef producers because of added complexity and requirements for considerable knowledge of environmental issues and management skills. This, in turn, reduces the value proposition for producers [180,193]. Addressing these challenges will require efforts to reduce implementation costs, increase transparency, improve standardization and simplify compliance requirements. Consistency of approach and language (standardized approach) is essential to facilitate adoption and collaboration across stakeholders. There is a need for policy certainty and to avoid real and perceived risks that changes in credentialing rules will occur too rapidly to allow viable engagement and response from businesses. Harrison [194] points out that most of the effort in developing mitigation strategies is performed by developed countries for developed countries, while GHG emissions from ruminant livestock are the greatest in low- to middle-income developing countries. The future holds a significant challenge to present a unified, transparent and consistent view of credential development, which will be globally relevant and include nations across the various income classes.

Having a centralized industry-led credentialing framework that is designed to be adaptable and updatable in a well-defined and expected manner will build confidence in its use by the Australian grass-fed beef industry. The governance of the framework would need to consider data management, conflict resolution, security and privacy requirements, as well as how data are used in functional processes such as benchmarking.

8.2.5. Recommendation 5: Developed to Use Digital Technologies and Scalable Methods

The methods, measurements and metrics used as key indicators in the credentialing platform should be selected, balancing the ease of use and the cost-effectiveness with the need to be accurate (with defined uncertainty), verifiable and operational. Defining uncertainty for remotely sensed data sources tends to be time-consuming and expensive, but there has been continual development and application of scientifically verified and published protocols relevant to climate and biodiversity (e.g., [195,196]). Potential options that align with these criteria are remote sensing or integration with existing record-keeping software and databases (e.g., Agtech products). New data layers and products based on remote sensing are being developed to meet the demand for cost-effective credentialing metrics. To support a credentialing platform, the metrics will have to be operational, sustainable and preferably accessible via an API. The accuracy and uncertainty of metrics should be understood through scientific verification, and metrics that have higher levels of uncertainty should be discounted accordingly. Some potential candidate tools are currently under development, at the proof-of-concept stage, and/or not yet commercially available products. Identifying and capturing supporting data likely to be used in future credentialing methods should be considered.

8.2.6. Recommendation 6: Based on Trusted Sources of Data, Informed by Scientific Evidence

By relying on high-quality data and methods, climate and biodiversity credentials for grass-fed beef production can accurately reflect the sustainability performance of beef producers. Incorporating scientific evidence into beef credentials will also foster collaboration between scientists, policymakers, industry stakeholders and service providers. Peer-reviewed literature and established scientific principles should guide the design and implementation of beef credentials to ensure a comprehensive and scientifically sound approach. Independent verification enhances transparency, reduces the risk of greenwashing and fosters consumer trust by offering assurance that the claims made by producers and retailers are based on verified data [3]. Credentialing should be integrated with the clear labeling of products so that consumers are correctly informed and respected as active actors in sustainability [197]. Credential platforms and providers also rely on specialist scientists to develop international consensus views on sustainability accounting [198,199]. Scientifically substantiated credentials enable consumers to identify beef products that align with their sustainability values, promoting the transparency throughout the supply chain and so incentivizing the adoption of sustainable practices by beef producers.

Within the scope of our review of SCA schemes, we have identified methods, measurements and metrics that are currently used, along with the associated verification for emissions accounting and sequestration and biodiversity (particularly whole-business habitat condition assessment). The level of uncertainty around the various metrics used should be determined. Some of the more recently developed remote sensing/machine learning methods offered are outputs from commercial providers, and the verification of the systems via accessible, peer-reviewed scientific evaluations is lacking, perhaps because of commercial IP concerns. Further, an inherent risk with remote-sensing-based products is the working life of satellite hardware. Suitable governance arrangements and technical contingencies were considered important to ensure the ongoing and timely supply of data for credentialing from remote sensing systems. For producers to substantiate their environmental credentials, the scheme-coordinating body will need to ensure that data providers verify product claims and have a secure data pipeline.

8.2.7. Recommendation 7: Applied with Central Governance but Cross-Sectoral Support

Trust in climate and biodiversity credentialing is more likely when undertaken within frameworks based on co-design, where the common problems of transition policy, largely around the lack of cross-sectoral support, have been addressed [200,201]. The importance of enabling central leadership of these processes was identified in the implementation of credentialing. In the case of the Australian grass-fed beef industry, peak industry representation for the red meat industry nationally may be an option, provided a suitable level of independence that is acceptable to target markets can be demonstrated. It would also be necessary to achieve recognition from, and coordination with, other interested parties such as producer groups, federal agencies and conservation groups. Getting credentialing governance right will ensure greater acceptance by local and international markets for grass-fed beef. There is also the need to avoid perverse outcomes, which are unintended and undesirable consequences that can arise from the implementation of a credentialing system, for example, gaming or strategic behavior, where participants strategically manipulate their practices to meet the credentialing criteria. A detailed review of perverse incentives in credentialing and the role of governance and response is outside the scope of this review but has been discussed by others [202].

For climate, protocols for credentials should be consistent with IPCC documents, peer-reviewed scientific literature, ERF methods and/or other published guidelines (e.g., Climate Active [39]). Biodiversity credentialing, similar to climate credentialing, should be consistent with peer-reviewed literature and global best practice (such as the Australian Farm Biodiversity Certification scheme [35], Accounting for Nature [16], and/or the underpinning framework used in Landscape Options and Opportunities Calculator for Biodiversity (LOOC-B) [52].

The review and modification of credentialing methods is an ongoing process. Credentialing schemes are devised to incentivize industries to adopt new practices, but when the adoption becomes a matter of common practice, then the need for an incentive is no longer there. An adaptive system should be developed (a) that favors the brave early adopters but (b) that can be adopted by producers across the spectrum of management skills and business infrastructure, rather than limited to large businesses that can outsource the process and implement changes to practice without major disruption to productivity. This has been evidenced by the disproportionate subscription of larger livestock businesses to ERF activities [150], so active efforts will be needed to ensure engagement across the sector. As described in the previous section, the longevity of data streams is also important, so technical aspects of data collection and curation need to be carefully planned.

8.2.8. Recommendation 8: Aligned with Business Objectives and a Strong Value Proposition

The uptake of a credentialing system by the grass-fed beef industry will rely on a clear value proposition aligned with business objectives or compliance with regulation. The benefits from credentialing for the industry will be market access, access to capital, social license and recognition of producer stewardship, product marketing, improved production efficiency and producers better equipped to engage with opportunities and scheme providers. However, the objective of supporting profitable beef production needs to be kept in mind; maintaining or increasing profitability is part of the value proposition. Engagement in the ERF scheme has been challenging for the livestock sector due to limited options for methods that address livestock management issues in an integrated manner. For example, the ERF has 1815 projects registered and has issued more than 127 million ACCUs, but only 14 projects relate to beef herd management, and of these, only 3 have been issues with ACCUs [150].

A tiered approach to credentials will enable flexibility for a broader segment of the industry to engage. However, for cattle producers to be motivated to engage and continue working to meet the requirements of the second and third tiers and then to consider other SCA schemes that may fit with business objectives, credentialing must be supported by a value proposition commensurate with the extra effort. The messaging and language used in communicating the tiered-credentials approach will be critical for adoption.

8.3. Methods and Metrics for Credentials

In many cases, there were several potential sources of data associated with various methods or models used to quantify climate and biodiversity indicators. Often, as the cost of implementing a method decreases, so does the accuracy and, consequently, confidence in the results. For example, the use of field-based methods that require specialist expertise to implement or validate will carry a high cost, whereas remote sensing methods can be applied at scale and much more cost-effectively. However, scaleable methods such as remote sensing can still be developed so that they are rigorous and scientifically substantiated (e.g., [195,196,197]). It is important that the accuracy of any method is well understood, as the credential may be increasingly discounted as the level of uncertainty for the measure increases [41].

Candidate measures identified that could support tiered credentialing for the areas of emissions/emissions intensity, sequestration and biodiversity are outlined in Table 6, Table 7 and Table 8. The metrics identified were prioritized based on (i) achieving a substantive impact for the credential, (ii) being an important assessment point for entry-level credentials and (iii) being ready for use in credentialing.

Table 6. Candidate measures identified to support tiered credentialing for emissions/emissions intensity.

Level	Measure	Methods	Data Quality	Scientific Confidence	Tier (s)
Learning	Course completion	Carbon accounting technical manual. MLA e-learning modules. Carbon EDGE.			Tier 1
Monitoring and Benchmarking	Herd structure Animal numbers Liveweight gain Sale numbers Sale weights Pasture quality	Farm Records	Med-High	High	Tiers 2/3
		SB-GAF	Medium	High
		Ruminati	Unknown	Unknown
		MLA Carbon Calculator	Unknown	Unknown
		AgCare	Unknown	Unknown
Management	Increase weaning /marking rate Reduce numbers while maintaining output Increase weaning to slaughter growth rate Breed for improved feed conversion efficiency Join heifers at earlier age Feed additives Anti-methanogenic pastures and supplements Fertilizer/Pesticide use	Farm Records /Statutory declarations	Med-High	High	Tiers 1/2/3

Table 6. Candidate measures identified to support tiered credentialing for emissions/emissions intensity.

Level	Measure	Methods	Data Quality	Scientific Confidence	Tier (s)
Learning	Course completion	Carbon accounting technical manual. MLA e-learning modules. Carbon EDGE.			Tier 1
Monitoring and Benchmarking	Herd structure Animal numbers Liveweight gain Sale numbers Sale weights Pasture quality	Farm Records	Med-High	High	Tiers 2/3
		SB-GAF	Medium	High
		Ruminati	Unknown	Unknown
		MLA Carbon Calculator	Unknown	Unknown
		AgCare	Unknown	Unknown
Management	Increase weaning /marking rate Reduce numbers while maintaining output Increase weaning to slaughter growth rate Breed for improved feed conversion efficiency Join heifers at earlier age Feed additives Anti-methanogenic pastures and supplements Fertilizer/Pesticide use	Farm Records /Statutory declarations	Med-High	High	Tiers 1/2/3

8.3.1. Emissions and Emissions Intensity

Enteric CH₄ emissions and land use change are key components in Australia’s grazing-based production systems that account for much of the GHG emissions from beef production. Other components may need consideration for aspects of the supply chain, such as feedlots [29]. Determining a basic estimate of enteric emissions can be achieved based on farm production records, as enteric emissions are closely related to the size and number of cattle and the quality of their diet (Table 6). The SB-GAF tool and digital variants based on SB-GAF are available to the public or through commercial consultancies for integrating production data to calculate total emissions and emissions intensity for sheep and beef businesses. They provide a comprehensive carbon accounting platform for entry-level credentials. Improvements in data management systems and software that reduce duplication in data entry should be prioritized to justify the effort in long-term repetitive annual assessment. The quality of data used to calculate emissions and emissions intensity should be medium–high, depending on record-keeping systems, while accounting confidence in some farm records (e.g., livestock numbers, live weight and growth to estimate enteric emissions) and the SB-GAF tool, which are supported by peer-reviewed publication, is high. Data quality refers to aspects of accuracy, reliability, verification, and governance of base data sources. For example, some farm records need to be accurate for purposes such as compliance audits, legal transactions (e.g., traceability documentation for livestock transport and sale) and taxation. Recommended measures for emissions and emissions intensity for beef production were whole-business CO₂-e and CO₂-e kg⁻¹ LW sold.

Table 7. Candidate measures identified to support tiered credentialing for sequestration.

Level	Measure	Methods	Data Quality	Scientific Confidence	Tier (s)
Learning	Course completion	Carbon E-learning Carbon 101 Trees on farm and shelterbelts		High	Tier 1
Monitoring and Benchmarking	Vegetation/Soil Organic Carbon	Baseline sampling (ERF)	High	High	Tiers 2/3
		FLINTpro	Uncertain	Uncertain
		FullCAM	Medium	High
		LOOC-C	Uncertain	High
		CIBO Labs	Unknown	Unknown
		FLINTpro	Uncertain	Unknown
		FullCAM	Uncertain	High
		LOOC-C	Medium	Uncertain
		SB-GAF	Uncertain	High
		Proximal/remote sensing	Medium	High
Management	Paddock trees area	Farm map/FLINTpro	High	High	Tier 1/2/3
	Remnant veg. area	Farm map/FLINTpro	High	High
	Enviro. Plantings area	Farm map/FLINTpro	High	High
	Inputs	Farm Records	High	High
	Grazing management /Rotations	CIBO Labs	Uncertain	Unknown

Table 7. Candidate measures identified to support tiered credentialing for sequestration.

Level	Measure	Methods	Data Quality	Scientific Confidence	Tier (s)
Learning	Course completion	Carbon E-learning Carbon 101 Trees on farm and shelterbelts		High	Tier 1
Monitoring and Benchmarking	Vegetation/Soil Organic Carbon	Baseline sampling (ERF)	High	High	Tiers 2/3
		FLINTpro	Uncertain	Uncertain
		FullCAM	Medium	High
		LOOC-C	Uncertain	High
		CIBO Labs	Unknown	Unknown
		FLINTpro	Uncertain	Unknown
		FullCAM	Uncertain	High
		LOOC-C	Medium	Uncertain
		SB-GAF	Uncertain	High
		Proximal/remote sensing	Medium	High
Management	Paddock trees area	Farm map/FLINTpro	High	High	Tier 1/2/3
	Remnant veg. area	Farm map/FLINTpro	High	High
	Enviro. Plantings area	Farm map/FLINTpro	High	High
	Inputs	Farm Records	High	High
	Grazing management /Rotations	CIBO Labs	Uncertain	Unknown

8.3.2. Sequestration

Carbon storage is a product of the area available for sequestration, and the sequestration rate of organic carbon in soil and vegetation. Perennial plantings, particularly shrubs and trees, are the primary mechanism for sequestering carbon within extensive livestock systems. Carbon stores and fluxes are measured as component pools (e.g., SOC) and integrated with models such as FullCAM, which is supported by peer-reviewed science. However, the technical skill required to handle the complexity of operating FullCAM means it is not recommended as a tool for entry-level assessments. Instead, Landscape Options and Opportunities Calculator for Carbon (LOOC-C) [45] is recommended as an exploratory tool to assess the potential for response and the range of methodologies likely to deliver the greatest impact prior to committing to the large-scale implementation of practice change. LOOC-C, the Landscape Options and Opportunities Calculator for Carbon, developed by CSIRO, is a simplified web-based or API implementation of the FullCAM model that is designed to support location-appropriate practices contributing to climate decision making and approved by ERF.

Suggested measures for entry-level credentialing are listed in Table 7. Data used for the monitoring and benchmarking of carbon stores are generally considered to be of medium quality, given that the models are typically based on complex assumptions and some IP restriction have prevented assessment. Methods and accounting systems that can be verified for data quality and scientific confidence are suitable for monitoring and/or benchmarking. For example, FLINTpro [44] is a web-based implementation of the FullCAM model (supported by peer-reviewed science). Therefore, this product should be suitable for entry-level credentialing but ideally should also be supported by peer-reviewed published validation in the absence of information on the fidelity of the implementation process. The measurement of revegetation areas based on farm maps or satellite imagery has a higher level of confidence, and measurement of carbon stocks could be consistent with established protocols, such as ERF. The recommended measures for carbon stores (CO_2-e as SOC and vegetation) for beef production were at the business level, and this may require the aggregation of estimates from areas under “business as usual” management, with estimates from carbon estimation areas where the new practice has been implemented. Alternatively, estimates could be for a subset of the business, property, whole of business, or combined businesses or properties.

8.3.3. Biodiversity

Producers are responsible for the short- and long-term management of vegetation in extensive beef systems, with subsequent effects upon ecosystem biodiversity. Further, land use change associated with agriculture poses a persistent threat to biodiversity locally and globally. A practical assessment of species for the purpose of quantifying biodiversity is extremely difficult, and a common approach is to evaluate the condition of the habitat, predominantly associated with the amount and quality of vegetation (Table 8). The use of remote sensing products for the scalable assessment of habitat conditions has been in practice for more than two decades. The integration of remote sensing with extensive collections of site-specific population surveys is an area that is rapidly developing [17,176,185] and has provided region-specific assessments across continental Australia. Similar methodologies have been developed for global assessments of biodiversity [203]. However, such tools require extensive development and calibration before they can be made available, generally after a peer-review process. Farm management practices, the retention of natural habitat, and the restoration of habitat can support positive biodiversity outcomes. A survey of practices, such as the Cool Farm Tool biodiversity assessment [204] or the Farm Sustainability Assessment protocol [105], can provide an efficient entry-level indication of biodiversity credentials. However, scientific confidence in outcomes may be uncertain unless validated during development, and the transferability of these European tools to the Australian context may be limited. An Australian equivalent questionnaire will be required as an entry point for surveying farm practices for biodiversity, calibrated to Australia’s unique flora and fauna and farming practices, to properly account for co-benefits. For example, conservation activities to control feral animals could be easily recorded, but the associated impacts on biodiversity will be more difficult to assess and must be made over longer timeframes. However, if feral animal control is also associated with improvements in agricultural production, e.g., lamb survival, it is likely that the practice will be maintained over longer timeframes, delivering a co-benefit to biodiversity rather than as a biodiversity-specific practice change.

In addition to understanding the interactions between practices and potential biodiversity impacts, tools that quantify the status of habitat conditions may help assess the magnitude of the impact of current practices, identify target areas for intervention and inform management for credentialing. LOOC-B [52], the Landscape Options and Opportunities Calculator for Biodiversity developed by CSIRO, is the recommended tool for the estimation of habitat conditions and other derived biodiversity metrics. It provides two operational modes, a retrospective (20 year) assessment of previous practice change and a forecast assessment (25 years) to evaluate the biodiversity performance of new changes in practice.

The recommended measure for biodiversity is the whole-business habitat condition, scaled from 0 “degraded” to 1.0 “natural”. Habitat connectivity is the connectedness of each location (grid cell) to the natural habitat in the surrounding landscape [205]. It is an indicator of mobility potential through natural environments necessary for species and genetic diversity. It is scaled from 0 to 1.0, where a value of 1.0 indicates the grid cell is in an intact reference state and is fully connected to a landscape where all other locations are also in an intact reference state. Biodiversity persistence is a third measure, predicting the number of presently supported species that can maintain their population into the future based on accepted long-term climate forecasts. Threatened-species habitat provision is the fourth indicator in LOOC-B. The contribution of habitat in a specified area to supporting nationally listed threatened species is estimated by combining information on the spatial distribution of threatened species with data on habitat condition. The locations in which nationally listed threatened species may occur, given a suitable habitat, were taken from the Species of National Environmental Significance database [206].

Table 8. Candidate measures identified to support tiered credentialing for biodiversity.

Level	Measure	Methods	Data quality	Scientific Confidence	Tier(s)
Training	Farm biodiversity awareness Biodiversity software awareness Course completion	Accounting for Nature BirdCast [206] SEEA			Tier 1
Questionnaire	Qualitative/Quantitative business details	Survey	Medium	Ongoing verification	Tiers 1/2/3
Monitoring and Benchmarking	Habitat condition # Biodiversity persistence # Habitat connectivity # Threatened species Habitat provision Balance tree/grass cover	LOOC-B LOOC-B LOOC-B LOOC-B CIBO Labs Field survey	Medium Medium Medium Medium Uncertain Uncertain	High High High High High High	Tiers 1/2/3
Management	Paddock trees area and trend	Farm map /FLINTpro	High	Medium	Tiers 1/2/3
	Remnant veg. area	Farm map /FLINTpro	High	High
	Runoff/riparian management	Farm map/Field	Medium	Low
	Fenced exclusion area	Survey/LOOC-B	High	Medium
	Enviro. Plantings area	Farm map	High	Medium
	Feral animal control	Farm map	High	Medium
	Weed control	Statutory declaration	High	Low
	Erosion control/Cover	Fractional cover /CIBO Labs/LOOC-B	High	High
	Fertilizer/Pesticide use	Statutory declaration	Medium	High

# Weighted average monitoring and management methods. Abbreviations: SEEA, System of Environmental-Economic Accounting, LOOC-B, Landscape options and opportunities calculator for biodiversity.

Table 8. Candidate measures identified to support tiered credentialing for biodiversity.

Level	Measure	Methods	Data quality	Scientific Confidence	Tier(s)
Training	Farm biodiversity awareness Biodiversity software awareness Course completion	Accounting for Nature BirdCast [206] SEEA			Tier 1
Questionnaire	Qualitative/Quantitative business details	Survey	Medium	Ongoing verification	Tiers 1/2/3
Monitoring and Benchmarking	Habitat condition # Biodiversity persistence # Habitat connectivity # Threatened species Habitat provision Balance tree/grass cover	LOOC-B LOOC-B LOOC-B LOOC-B CIBO Labs Field survey	Medium Medium Medium Medium Uncertain Uncertain	High High High High High High	Tiers 1/2/3
Management	Paddock trees area and trend	Farm map /FLINTpro	High	Medium	Tiers 1/2/3
	Remnant veg. area	Farm map /FLINTpro	High	High
	Runoff/riparian management	Farm map/Field	Medium	Low
	Fenced exclusion area	Survey/LOOC-B	High	Medium
	Enviro. Plantings area	Farm map	High	Medium
	Feral animal control	Farm map	High	Medium
	Weed control	Statutory declaration	High	Low
	Erosion control/Cover	Fractional cover /CIBO Labs/LOOC-B	High	High
	Fertilizer/Pesticide use	Statutory declaration	Medium	High

# Weighted average monitoring and management methods. Abbreviations: SEEA, System of Environmental-Economic Accounting, LOOC-B, Landscape options and opportunities calculator for biodiversity.

9. Conclusions

As land custodians and managers, farmers play a central role in jointly managing climate (emissions and sequestration) and biodiversity outcomes. This review describes the implementation of design criteria that were developed through stakeholder consultation and provides recommendations for implementing climate and biodiversity credentials in Australian grass-fed beef production. Priority metrics for climate, carbon sequestration and biodiversity credentialing were identified. Recommendations were aimed toward facilitating industry participation at the entry level and allow flexibility to adapt to evolving markets and to incorporate advancements in technology. The uptake of such credentials by beef producers will be influenced by factors related to their business, and the design and implementation of the credentialing system play a crucial role. Confidence in the value of achieving credentials, ease of implementation and a strong value proposition as an incentive were all significant factors for the expansion of credentials in grass-fed beef production. Our recommendations consider the evolving climate and biodiversity credential markets, anticipating advancements in technology, increased incentives, and the use of tiered credentials to facilitate industry participation. Being guided by these design criteria in consultation with industry stakeholders improves the prospect that a co-designed credentialing system can drive positive change and contribute to the industry’s environmental sustainability goals. Ongoing improvement and alignment with scientific advancements remain key for the continued success of climate and biodiversity credentials in the grass-fed beef sector.