Accurate detection of land degradation in semi-arid environments requires approaches that distinguish persistent ecosystem degradation from short-term climatic variability. This study developed and evaluated a multi-sensor machine-learning framework integrating Landsat-8 optical imagery, Sentinel-1 Synthetic Aperture Radar (SAR), environmental variables, and long-term vegetation monitoring data to map land degradation risk in Camdeboo National Park, South Africa. Vegetation cover observations from 52 permanent monitoring plots were integrated with spectral vegetation indices, SAR backscatter, terrain attributes, and climatic variables within a Random Forest (RF) regression framework. Model performance was compared with Stepwise Multiple Linear Regression (SMLR) using five-fold spatial cross-validation, independent validation, and multiple performance metrics, including R2, RMSE, relative RMSE, MAE, MAPE, mean bias error, Nash–Sutcliffe Efficiency, Lin's Concordance Correlation Coefficient, residual diagnostics, Bland–Altman analysis, and prediction intervals. The RF model substantially outperformed SMLR, explaining approximately 78% of the observed variability in bare soil compared with 51–55% for the linear benchmark while consistently producing lower prediction errors and reduced bias. Seasonal analyses revealed higher vegetation cover and lower bare-soil exposure during the wet season, whereas dry-season conditions exhibited increased surface exposure. Persistent degradation hotspots were concentrated in valley-bottom plains, drainage lines, and areas adjacent to settlements, reflecting the combined influence of topography, grazing pressure, and climatic stress. Vegetation indices (NDVI, SAVI, and GNDVI), Sentinel-1 SAR backscatter, soil moisture, temperature, and terrain variables emerged as the most influential predictors. Integrating seasonal climatic context with multi-sensor observations reduced the risk of confusing drought-induced vegetation decline with structural land degradation. The proposed framework provides a robust and transferable decision-support tool for long-term land degradation monitoring and sustainable management of semi-arid protected landscapes.

South Africa is a water-scarce country predominantly practicing dryland agriculture, relying on rainfall onset to determine planting date. Sunflower is commonly considered a substitute crop, planted when primary crops face delayed plantings. The interaction between crop development and environmental variability is critical in Southern Africa because projections indicate warming of up to twice the rate of the global average. We investigated sunflower planting dates and production across two austral summer seasons (2020/2021 and 2021/2022) and two provinces of South Africa. A widely grown cultivar was sown monthly through the summer (from November to March) in a split-plot design. Plant height and leaf number were recorded weekly. Plants were harvested at physiological maturity for morphological and yield assessments. The hotter, drier first season (2020/2021 austral summer) led to the plantings reaching physiological maturity approximately 25 days earlier than in the wetter, cooler season (2021/2022 austral summer). In the hot/dry season, seed yield and quality were lower but more stable across planting dates. In the wetter/cooler second season, there were sharp declines in yield (78.8 g/plant, equivalent to 3.2 tons/ha ) and greater variation in oleic acid (up to 59.9%) across planting dates. These results highlight sunflowers’ stability under hot, dry conditions, supporting their use as a substitute crop.

Understanding seasonal variability and development of skilful seasonal climate forecasts (SCFs) is key in mitigating climate-related risks, including helping to support adaptation to climate change and variability. The purpose of this study is to consider possible factors influencing the predictability of maximum temperature SCFs in southern Africa. To address this question, two hypotheses are tested: namely (1) There is skill in making maximum temperature forecasts in the Southern African Development Community (SADC); and (2) The skill is contributed by two main attributes-ENSO-related climate variability and anthropogenic climate change-as a result, temperature forecasts are worth taking into account in pre-season decision-making. A state-of-the-art global climate model's atmospheric thickness fields are statistically downscaled to maximum temperatures for the austral spring to autumn period. Forecast performance over a 24-year period is evaluated for both original and for linearly detrended temperature data. The verification results indicate that predictive skill for maximum temperatures reflects the combined influence of ENSO-related variability and long-term anthropogenic warming trends. The majority of the skill is not, however, a consequence of warming trends, since the climate model is able to predict the seasonal-to-interannual maximum temperatures variation skilfully, without assistance from temperature trends. Detrending data improves probabilistic skill, suggesting that removing trends helps isolate the seasonal signal, enhancing the models' reliability and discrimination of probabilistic maximum temperature SCFs. However, deterministic skill declines, revealing long-term climate trends' influence on the apparent accuracy of deterministic forecasts. The trend thus influences understanding of forecast performance and needs to be considered when conveying how good a forecasting system is.

Whilst skilful seasonal climate forecasts are routinely produced, their ability to support profitable agricultural decision-making remains uncertain, particularly in regions with modest seasonal predictability and high climate variability. We assess the financial implications of using a statistically derived seasonal maize crop-yield forecast for a medium-size commercial farm in South Africa, focusing on how forecast attributes interact with farmer investment strategies. A cumulative profit framework is used to evaluate three stylised strategies representing different levels of risk exposure under forecast uncertainty. The crop-yield forecasts exhibit measurable skill but limited reliability, notably underpredicting the likelihood of ‘normal’ crop-yield seasons – and this reliability bias has important financial consequences. Reinvesting all available capital can be highly profitable when forecasts are mostly accurate, but leads to catastrophic losses when forecasts are given with a high degree of confidence, but are ultimately inaccurate. Conversely, partial reinvestment offers greater resilience to forecast errors, while a fixed annual investment strategy often produces the most stable long-term outcomes. Riskier strategies are most profitable when forecast weaknesses are avoided. These results demonstrate that even highly skilful seasonal yield forecasts can produce adverse financial outcomes if forecast reliability and decision risk are not explicitly considered. Aligning investment strategies with forecast attributes (such as reliability) and risk tolerance, and complementing standard forecast verification with simple financial metrics, is essential for effective agricultural climate services.

Sunflower (Helianthus annuus) is an oilseed crop of global economic importance, and South Africa ranks among the 20 top producers worldwide. Sunflower production can be severely limited by fungal, viral and bacterial diseases. In South Africa, knowledge of viral diseases in sunflowers is particularly limited. During a disease survey of a field trial for a separate study, we observed symptoms not common in sunflowers in South Africa on several plants across the trial. This study aimed to identify the causal agent of these symptoms that were observed on sunflowers in two consecutive seasons at two experimental sites in South Africa (Pretoria and Potchefstroom). Illumina sequencing of total RNA from symptomatic leaves and reverse transcription-PCR confirmation showed the presence of bidens mottle virus (BiMoV) in infected plants. BiMoV is a widespread potyvirus that is vectored by aphids, with weeds acting as viral reservoirs. The effects of the viral infection on the floral, morphological and yield traits in sunflowers were investigated. Pollen viability was reduced by 17.0%, plant height by 16.7%, leaf number by 12.3% and overall yield by 80.6%. This study suggests the potential for a significant impact from BiMoV infection on sunflower development and yield in South Africa. This is only the second report of natural infection of BiMoV in sunflowers and the first report of BiMoV in sunflowers in South Africa. We present preliminary evidence for yield losses; management strategies and disease progression need to be further investigated.

South Africa’s climate studies generally focus on coarser provincial levels, which aid policy recommendations, but have limited application at the farm level. District level climate studies are essential for farmer participation in climate change mitigation strategies and management. Our study aimed to investigate historical climate data for trends and their influence on maize yields at the magisterial level. Six sites were selected from three major maize-producing provinces in South Africa: Mpumalanga, Northwest, and Free State. Magisterial districts in each province were selected from different Köppen-Geiger climate zones. The climate variables assessed by the Mann–Kendall trend test included maximum or minimum temperature, rainfall, number of extreme high-temperature days, rainfall onset and cessation from 1986 to 2016. The average maximum temperatures were observed to have significant upward trends in most locations, except for Schweizer-Reneke and Bethlehem. The fastest rate of change was observed at Klerksdorp (0.1 °C per 30 years of study), while the Schweizer-Reneke district was the slowest (0.05 °C per 30 years of study). No significant changes were observed in rainfall onset, cessation, or total rainfall in Schweizer-Reneke, Standerton, and Bethlehem, which are scattered across the different provinces. The other districts in each province showed significant changes in these parameters. Rainfall accounted for the significant variation in maize yields over the study period, explaining between 18 and 40

Aridification threatens over 2.3 billion people by reshaping landscapes and increasing socio-economic vulnerabilities, demanding immediate policy actions and global cooperation to enhance resilience and develop transformative solutions.

Climate model projections are increasingly being included within adaptation planning across sectors but there is limited understanding of how they are being used, and to what extent they improve adaptation planning. This article investigates how climate projections inform adaptation planning processes in the National Communications (NCs) to the United Nations Framework Convention on Climate Change (UNFCCC) in 16 southern African countries through a document analysis together with 18 key informant interviews. The study found that all the NCs include future climate model projections for the mid and/or late twenty-first century and focus on average changes in temperature and precipitation; meanwhile, the models, scenarios and time periods used vary between countries. The climate analysis is often detached from the adaptation planning section of the NC. The impacts and adaptation sections focus on key risks, such as flooding and drought and have limited recognition of uncertainties, suggesting plans are made without considering the full range of plausible futures. The role of climate science in the adaptation planning process varies, with some evidence of highly collaborative processes, resulting in evidence-based adaptation options across sectors and scales. In many cases, boundary agents play a key role in interpreting and communicating climate projections. We suggest that providing additional climate projections is unlikely to improve national adaptation planning, despite their scientific benefits. Instead, the focus should be on developing approaches and collaborative processes to distil and interpret climate information in different contexts, to enable decision-makers to understand the range of plausible futures, including changes in climate alongside growing populations, urbanization and changing economies.

We have committed to ambitious targets under the Global Biodiversity Framework, but projected climate change makes the achievement of many of these targets extremely difficult and will effectively require a significant rethinking in how to achieve multiple targets. In this Opinion, we have chosen to focus on selected targets, considering how their achievement is likely to be compromised by climate change but also what the possibility of real response options might be. We focus on restoration (Target 2), spatial planning and integration (Targets 1, 2, 3 and 10), sustainable use and sustainable benefits to people (Targets 5, 9 and 10) and, finally, equity and social justice (Targets 13, 20-23 and Goal C). Now more than ever, the window for effective action on climate change and biodiversity is closing, requiring rapid and, most importantly, collective action.

The high spatial variability of precipitation, heightened frequency of droughts and concomitant increases in exposure to water stress across southern Africa due to climate change, presents significant challenges for sugarcane production and the regional sugarcane production value chain. While production has intensified in the past few decades, yields have declined due to increased climatic variability and agronomic management approaches. Increased precipitation variability has enhanced sugarcane vulnerability to water stress and is likely to negatively affect yields. Combining crop simulations and relationships between sugarcane water use and observed rainfall, we introduce a crop productivity ratio (CPR) which assesses sugarcane water stress for six sugarcane mills across southern Africa. The CPR and simulation results were used to assess the adaptation potential or ‘space’ for mill areas that have varying rates of exposure and abilities to adapt to water stress. Simulation results were used to determine the long-term adaption potential of mill areas and to surmise the causes of yield declines. The results were used to offer recommendations to reduce vulnerabilities and enhance adaptation to water stress. We conclude that the amplification of inter-annual precipitation variability will enhance the exposure of sugarcane to water stress and require adaptation interventions. Adapting to external shocks is a multifaceted exercise that requires a holistic approach that includes every aspect of the sugarcane value chain.

Environmental and climatic factors, as well as host demographics and behaviour, significantly influence the exposure of herbivorous mammalian hosts to pathogens such as Bacillus anthracis, the causative agent of anthrax. Until the early 1990s in Kruger National Park (KNP), kudu (Tragelaphus strepsiceros) was the host species most affected by anthrax, with outbreaks occurring predominantly in the dry season, particularly during drought cycles. However, the most affected host species has shifted to impala (Aepyceros melampus), with more frequent anthrax outbreaks during the wet season. This study investigates the roles of environmental variation and other host species in this shift. Temporal trends in environmental variables such as precipitation, soil moisture, temperature, and normalised difference vegetation index (NDVI) were analyzed in relation to anthrax occurrence (presence/ absence and counts). Additionally, correlations between host species’ densities and anthrax mortalities over time were examined. Anthrax cases in 1990 were concentrated in the central and northern regions of KNP(excluding Pafuri), primarily affected kudus; while subsequent mortalities affected mostly impala and were restricted to the far north, in Pafuri. Significant correlations were found between kudu anthrax mortality and a decrease in NDVI, average temperature, SPI-6 and SPI-12 (Standardised Precipitation Index in various time intervals. Conversely, anthrax occurrence in impalas was associated with a decline in SPI-3, and temperature rise, with increased mortality during the rainy season. Elephant density correlated negatively with kudu mortality, but a positive correlation with both impala mortality and impala density. The study concludes that environmental variables and species’ densities may alter the diversity and frequency of hosts exposed to B. anthracis. Climate extremes and alterations therein may exacerbate anthrax severity by modifying species susceptibility and their probability of exposure over time.

The nature of science involves the discovery of unknowns. Questions are raised, hypotheses are developed and tested, results are analyzed, and conclusions are made from studies and observations. For thousands of years, this process has steadily advanced human knowledge of our world. Conversely, the lack of study can lead to unwanted consequences (e.g., the impacts of lead paint and asbestos in building construction). Currently, Earth is undergoing a unique experiment through anthropogenic global warming. Many negative impacts are already being observed (e.g., increased heatwaves, flooding, and droughts), and others are hypothesized. However, the potentially most disruptive changes associated with climate change may not even be imagined. The changing climate interacts with hundreds of other constantly evolving environmental shifts (e.g., atmospheric CO2, nitrogen deposition, ozone, landuse change) in ways that have never previously occurred (i.e., nonantecedent factors). The factors could interact to produce events that humans have never seen (i.e., nonantecedent events). These events may be the most troubling because we do not have a historical context from which to predict and prepare for their occurrence. This chapter examines how nonantecedent factors and events interact and how we might better predict (and therefore prepare) their likelihood of happening.

Sclerotinia head rot, caused by Sclerotinia sclerotiorum, is a major disease limiting sunflower production in tropical and subtropical agroecological zones. Sporadic outbreaks across South Africa have resulted in major losses, yet little is known about the in-field climatic factors driving this infection. Short-interval, staggered plantings have been proposed as a control method for Sclerotinia head rot, which help to limit the number of plants in a susceptible developmental stage during conducive environmental conditions. However, this complicates field management practices, especially if working at the fringes of a planting window due to delayed rains. This study aimed to investigate the effect of planting date on Sclerotinia head rot progression in monthly plantings across the summer period. Artificial mycelial plug inoculations were performed at the R5.9 flowering stage in an open field. Disease establishment, progression and severity were monitored at 3-day intervals for 30 days. We show that disease establishment was delayed by low relative humidity or extreme low temperatures in the January and March planting dates where the first lesions were only observed 6 days post-inoculation. Consistently high temperatures above 27 degrees C also suppressed disease progression and produced low area under the disease progress curve (AUDPC) scores of 75.15 and 29.4 for the October and November planting dates, respectively. These findings suggest that regardless of season or location, selecting a planting date that ensures the sunflower bloom period aligns with the hottest, driest part of the season will probably suppress Sclerotinia head rot in regions with average summer highs above 27 degrees C. Local temperature and humidity at different planting dates significantly influence Sclerotinia head rot in sunflower, with temperatures above 27 degrees C suppressing disease progression in the flower head.image

Drought is one of the most hazardous natural disasters in terms of the number of people directly affected. An important characteristic of drought is the prolonged absence of rainfall relative to the long-term average. The intrinsic persistence of drought conditions continuing from one month to the next can be utilized for drought monitoring and early warning systems. This study sought to better understand drought probabilities and baselines for two agriculturally important rainfall regions in the Western Cape, South Africa – one with a distinct rainfall season and one which receives year-round rainfall. The drought indices, Standardised Precipitation and Evapotranspiration Index (SPEI) and Standardised Precipitation Index (SPI), were assessed to obtain predictive information and establish a set of baseline probabilities for drought. Two sets of synthetic time-series data were used (one where seasonality was retained and one where seasonality was removed), along with observed data of monthly rainfall and minimum and maximum temperature. Based on the inherent persistence characteristics, autocorrelation was used to obtain a probability density function of the future state of the various SPI start and lead times. Optimal persistence was also established. The validity of the methodology was then examined by application to the recent Cape Town drought (2015–2018). Results showed potential for this methodology to be applied in drought early warning systems and decision support tools for the province.

Meeting the needs of multiple users and uses of freshwater resources is becoming progressively challenging. The response to the 2015–2018 Western Cape drought in South Africa offers lessons for both commercial crop growers and policymakers to enhance resilience. The drought highlights the complex interactions between water supply for urban and agricultural uses. This study employed a mixed-methods approach by combining the five capitals (natural, physical, financial, human, and social) of the sustainable livelihoods framework with semi-structured interviews to assess the impacts of the hydrologic and socio-economic drought on irrigated apple production. Data used for the study included production statistics, dam and water flow, weather data, and interviews. Results highlight a progressive weakening of the natural and physical capital between 2015 and 2018. Human capital in the form of expert consultants together with social capital of networks proved key to mitigating the impact of drought on apple production. The study also found that growers’ adaptive capacity was high as they made use of multiple capitals available to them. This resulted in lower than anticipated impacts on production and in turn stabilized financial capital available to farmers. Lessons from the drought show that building human and social capital can significantly improve the resilience of commercial farms which form part of complex water systems. Urban water-related vulnerabilities and demand are closely interlinked with the vulnerability and adaptive capacity of irrigated agriculture. Thus, policies which facilitate the in-tandem adaptation of these sectors are likely to be most successful in building resilience.

It has been a turbulent year for the global climate on many levels.The dramatic impacts of climate change on the earth systems, including extreme weather events, continue to manifest [1].Meanwhile, geopolitical tensions, economic pressures, and stretched energy systems have been increasingly evident, often interacting in challenging ways.Whilst COP27 in Sharm El-Sheikh made only marginal progress in abating greenhouse gas emissions, it did deliver a significant and hopeful advance on loss and damage [2,3].This year has also been notable for a growing recognition of the need for interlinked action on climate and biodiversity, for example through incorporation of a climate target in the post-2020 Global Biodiversity Framework [4], and of the need for integrated research and policy programmes to address the nexuses between climate and food, water and security.Against this global backdrop, PLOS Climate has had an extraordinary first year as a new venue for peer-reviewed climate research.Since our first articles were published in February 2022 and we set ourselves a crucial mission [5], we've been delighted to see the journal develop into a flourishing, energetic worldwide community of authors, reviewers and editors.We have published articles across our broad and multidisciplinary scope, from basic climate science through to research on policy and governance at local to global scales.This wealth of original research has been accompanied by a series of timely Reviews, and by thoughtfully-written Opinions that have addressed current issues in climate science, policy and practice, and identified priorities for future research.We've also been driving our mission forward by reaching out to those global and regional communities we aim to serve, whether that be directly, or through partners and collaborators across the world.We will continue to prioritise making PLOS Climate a truly inclusive home for research from all regions.It has been a privilege to connect with researchers and practitioners working across the climate space at conferences, through visits to institutions and online events, and to hear direct from them how we can best meet their needs.We have particularly enjoyed opportunities to speak to early career researchers and hear their particular perspectives-not just on the substance of their research, but also on their experiences in academia and publishing.We look forward to partnering closely with them in future activities.One of our key areas of focus has been the interface between research and policy, and we have been working hard with our editorial board to explore ways in which PLOS Climate can connect scientific research with policy-and decision-makers, and provide a forum for discussion of research-policy interactions.This will remain an important priority for the journal in 2023 and beyond, and we hope to continue building a network of connections with stakeholders across this interface.Furthering Open Science is a fundamental part of PLOS Climate's mission, and we have relished the opportunity to discuss prospects for enhancing openness in climate research, including in a number of conference sessions we have either organised or contributed to this year.

Significance: A recent report from the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) assessed how the sustainable use of wild species benefits people and nature, and which policies work best to prevent unsustainable exploitation. In the context of an accelerating and alarming biodiversity crisis, the assessment findings have important implications for South Africa, a megadiverse country with a population that relies extensively on the use of wild species for food, energy, medicine, and income, amongst many other purposes. This Commentary reflects on implications of the IPBES assessment for South Africa, drawing on insights from local contributing authors.