Climate change and Australia's primary industries: factors hampering an effective and coordinated response.

Australia's primary production sector operates in one of the world's most variable climates with future climate change posing a challenge to its ongoing sustainability. Recognising this, Australia has invested in understanding climate change risks to primary production with a substantial amount of research produced. Recently, focus on this research space has broadened, with interests from the financial sector and expanded scopes of works from government and industry. These expanded needs require sector- and country-wide assessments to assist with the implementation of climate strategies. We considered the applicability of the current research body for these needs by reviewing 188 peer-reviewed studies that considered the quantitative impacts of climate change on Australia's primary industries. Our broad review includes cropping, livestock, horticulture, forestry and fisheries and biosecurity threats. This is the first such review for Australia, and no other similar country-wide review was found. We reviewed the studies through three lenses, industry diversity, geographic coverage and study comparability. Our results show that all three areas are lacking for sector- and country-wide assessments. Industry diversity was skewed towards cropping and biosecurity threats (64% of all studies) with wheat in particular a major focus (25% of all studies). Geographic coverage at a state level appeared to be evenly distributed across the country; however, when considered in conjunction with industry focus, gaps emerged. Study comparability was found to be very limited due to the use of different historical baseline periods and different impact models. We make several recommendations to assist with future research directions, being (1) co-development of a standard set of method guidelines for impact assessments, (2) filling industry and geographic knowledge gaps, and (3) improving transparency in study method descriptions. Uptake of these recommendations will improve study application and transparency enabling and enhancing responses to climate change in Australia's primary industries.

Future climate impacts on forest growth and implications for carbon sequestration through reforestation in southeast Australia.

Reforestation is identified as one of the key nature-based solutions to deliver carbon dioxide removal, which will be required to achieve the net zero ambition of the Paris Agreement. However, the potential for sequestration through reforestation is uncertain because climate change is expected to affect the drivers of forest growth. This study used the process-based 3-PG model to investigate the effects of climate change on development of above-ground biomass (AGB), as an indicator of forest growth, in regenerating native forests in southeast Australia. We investigated how changing climate affects AGB, by combining historical data and future climate projections based on 25 global climate models (GCMs) for the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways. We found that the ensemble means of 25 GCMs indicated an increase in temperature with large variations in projected rainfall. When these changes were applied in 3-PG, we found an increase in the simulated AGB by as much as 25% under a moderate emission scenario. This estimate rose to 51% under a high emission scenario by the end of the 21st century across nine selected sites in southeast Australia. However, when CO2 response was excluded, we found a large decrease in AGB at the nine sites. Our modelling results showed that the modelled response to elevated atmospheric CO2 (the CO2 fertilization effect) was largely responsible for the simulated increase of AGB (%). We found that the estimates of future changes in the AGB were subject to uncertainties originating from climate projections, future emission scenarios, and the assumed response to CO2 fertilization. Such modelling simulation improves understanding of possible climate change impacts on forest growth and the inherent uncertainties in estimating mitigation potential through reforestation, with implications for climate policy in Australia.

Modelling the effects of cold temperature during the reproductive stage on the yield of chickpea (Cicer arietinum L.).

During the reproductive stage, chilling temperatures and frost reduce the yield of chickpea and limit its adaptation. The adverse effects of chilling temperature and frost in terms of the threshold temperatures, impact of cold duration, and genotype-by-environment-by-management interactions are not well quantified. Crop growth models that predict flowering time and yield under diverse climates can identify combinations of cultivars and sowing time to reduce frost risk in target environments. The Agricultural Production Systems Simulator (APSIM-chickpea) model uses daily temperatures to model basic crop growth but does not include penalties for either frost damage or cold temperatures during flowering and podding stages. Regression analysis overcame this limitation of the model for chickpea crops grown at 95 locations in Australia using 70 years of historic data incorporating three cultivars and three sowing times (early, mid, and late). We modified model parameters to include the effect of soil water on thermal time calculations, which significantly improved the prediction of flowering time. Simulated data, and data from field experiments grown in Australia (2013 to 2019), showed robust predictions for flowering time (n = 29; R2 = 0.97), and grain yield (n = 22; R2 = 0.63-0.70). In addition, we identified threshold cold temperatures that significantly affected predicted yield, and combinations of locations, variety, and sowing time where the overlap between peak cold temperatures and peak flowering was minimal. Our results showed that frost and/or cold temperature-induced yield losses are a major limitation in some unexpected Australian locations, e.g., inland, subtropical latitudes in Queensland. Intermediate sowing maximise yield, as it avoids cold temperature, late heat, and drought stresses potentially limiting yield in early and late sowing respectively.

Unexpected increases in soil carbon eventually fell in low rainfall farming systems.

Understanding the drivers of soil organic carbon (SOC) change over time and confidence to predict changes in SOC are essential to the development and long-term viability of SOC trading schemes. This study investigated temporal changes in total SOC, total nitrogen (N), and carbon (C) fractions (particulate organic carbon - POC, resistant organic carbon - ROC and humus organic carbon - HOC) over a 16-year period for four contrasting farming systems in a low rainfall environment (424 mm) at Condobolin, Australia. The farming systems were 1) conventional tillage mixed farming (CT); 2) reduced tillage mixed farming (RT); 3) continuous cropping (CC); and 4) perennial pasture (PP). The SOC dynamics were also modelled using APSIM C and N modules, to determine the accuracy of this model. Results are presented in the context of land managers participating in Australian climate change mitigation schemes. There was an increase in SOC for all farming systems over the first 12 years (total organic C, TOC% at 0-10 cm increased from 1.33% to 1.77%), which was predominately in the POC% fraction (POC% at 0-10 cm increased from 0.14% to 0.5%). Between 2012 and 2015, there was a decrease in SOC back to starting levels (TOC = 1.22% POC = 0.12% at 0-10 cm) in all systems. The PP system had higher TOC%, POC% and HOC% levels on average and higher SOC stocks to 30 cm depth at the final measurement in 2015 (PP = 30.43 t C ha-1; cropping systems = 23.71 t C ha-1), compared to the other farming systems. There was a decrease in TN% over time in all farming systems except PP. The average C:N increased from 14.1 in 1999 to 19.7 in 2012, after which time the SOC levels decreased and C:N dropped back to 15.8. The temporal change in SOC was not able to be represented by the AusFarm model. There are three important conclusions for policy development: 1) monitoring temporal changes in SOC over 12 years did not indicate long-term sequestration, required to assure "permanence" in SOC trading (i.e. 25-100 years) due to the susceptibility of POC to degradation; 2) without monitoring SOC in reference land uses (e.g. CT cropping system as a control in this experiment) it is not possible to determine the net carbon sequestration, and therefore the true climate change mitigation value; and 3) modelling SOC using AusFarm/APSIM, does not fully represent the temporal dynamics of SOC in this low rainfall environment.

Late planting has great potential to mitigate the effects of future climate change on Australian rain-fed cotton.

The rain-fed cotton industry in Australia is vulnerable to climate change due to its high dependence on seasonal climate and summer rainfall. The rain-fed cotton in eastern Australia is increasingly being incorporated into cereal crop rotations due to government regulation of water resources, restricting opportunities for irrigated cotton. The accurate quantification of future climate impacts on exposed cropping systems such as rain-fed cotton is required to identify effective agronomic practices and inform strategic industry planning for the expansion of Australian cotton industry. Our study utilized 32 General Circulation Model (GCMs) for four cotton-growing regions representing the geographic range of cotton production in eastern Australia. We assessed the climate impacts on rain-fed cotton yield for two future periods (2040s and 2080s) under the RCP4.5 (low) and RCP8.5 (high) emissions scenarios employing the processed-based APSIM-Cotton model. Our results showed that current cotton yields varied with planting date, and the magnitude of yield change was consistent with regional climate variations at four locations representing the current geographic distribution of rain-fed cotton production. Means from multi-GCM ensemble showed growth period temperature increased more under RCP8.5 in the longer-term (2080s). Growth period rainfall changes had significantly positive effects on yield at all planting dates over each site. The projected increases in rainfall were more evident at later planting dates for dry sites than early planting dates at wet sites. In addition, we found planting date had the greatest influence on cotton yield at wet sites, while GCMs accounted for a large portion of variation in cotton yield at dry sites. We conclude that later planting has a great potential to increase rain-fed cotton yields. This provides important insights for regional-specific adaptation strategies for the rain-fed cotton industry in eastern Australia.