Increasing Climate Variability Research Articles

Machine Learning Model Development to Predict Power Outage Duration (POD): A Case Study for Electric Utilities

In the face of increasing climate variability and the complexities of modern power grids, managing power outages in electric utilities has emerged as a critical challenge. This paper introduces a novel predictive model employing machine learning algorithms, including decision tree (DT), random forest (RF), k-nearest neighbors (KNN), and extreme gradient boosting (XGBoost). Leveraging historical sensors-based and non-sensors-based outage data from a Turkish electric utility company, the model demonstrates adaptability to diverse grid structures, considers meteorological and non-meteorological outage causes, and provides real-time feedback to customers to effectively address the problem of power outage duration. Using the XGBoost algorithm with the minimum redundancy maximum relevance (MRMR) feature selection attained 98.433% accuracy in predicting outage durations, better than the state-of-the-art methods showing 85.511% accuracy on average over various datasets, a 12.922% improvement. This paper contributes a practical solution to enhance outage management and customer communication, showcasing the potential of machine learning to transform electric utility responses and improve grid resilience and reliability.

Alcon Blues: recent shifts in limiting habitat factors challenge the persistence of an endangered butterfly

AbstractInsect habitat specialists have declined more than generalists over the last decades. Understanding how habitat requirements and increased climate variability interact to explain persistence of populations is needed to enable effective conservation measures. Habitat specialists with a complex life cycle, such as myrmecophilous butterflies, are likely to be most vulnerable. Here, we explored to what extent the habitat factors explaining population persistence of the Alcon blue (Phengaris alcon), changed over a 25-year period in the Netherlands, contrasting the recent years 2018–2022 with extreme droughts with the preceding period 1998–2017 characterized by occasional climatic extremes. Population persistence of P. alcon over 1998–2017 as explained by historical habitat conditions was significantly higher in large heathland areas with large patches of its host plant Gentiana pneumonanthe. On the basis of current conditions, population persistence until 2017 was best explained by a combination of host plant area and quality. In contrast, persistence over the recent drought years was most closely associated with increasing occupancy of the optimal host ant Myrmica ruginodis and lower occupancy of competitive and predatory Lasius ants.Implications for insect conservation We conclude that critical habitat conditions change under increasing climatic extremes and that the availability of sufficient optimal host ants has become more critical than that of host plants. The results emphasise that both large-scale hydrological restoration and small-scale management for heterogeneity are necessary to preserve P. alcon and its habitat in the Netherlands. This is also likely to apply to other habitat specialists with complex life cycles from threatened habitats.

Adaptive Responses and Resilience of Small Livestock Producers to Climate Variability in the Cruz Verde-Sumapaz Páramo, Colombia

Enhanced anthropogenic climatic variability challenges small farmers. In the Sumapaz páramo (Colombia), higher irregularity in precipitation and temperature reduces the quality of pasture and cattle health. Data from surveys, semi-structured interviews, and focus groups were analyzed to understand livestock farmers’ responses to the impacts of climatic variability. To estimate the communities’ resilience in the páramo, we used the capitals framework, the Baseline Resilience Indicator for Communities (BRIC), and cluster analysis. The responses of most households aim to reduce the impacts of climatic variability on the production system, chiefly intensifying practices such as the rotation of paddocks, livelihood diversification, purchase of grass, and buying and selling livestock. Interestingly, farmers did not recognize the value of the types of capital for responding to climatic variability. Results showed that the use of available physical, social, and economic capitals render the farming system resilient. Our probit model estimated that economic and human capitals are the largest and most significant contributors to communities’ capacity to respond to climatic variability. However, pre-existing non-climatic vulnerabilities are also important. For example, poverty hinders farmers from using their income in response to climatic variability. The place-based measurements used in this research are easily understood and applicable by local policy makers to address increasing climate variability.

Overcoming systemic and institutional challenges in policy implementation in South Africa's water sector

The water sector in South Africa is faced with numerous challenges, among which include; increased flooding and prolonged droughts caused by increased climate variability, rapid population growth, unsustainable water demands and withdrawals by various water users, deficiencies in institutional management and infrastructural maintenance, lack of political will with accompanying high levels of corruption and steady deteriorations in all sub-sectors of the economy. Other significant challenges include provision of water in rural communities, water pollution especially from poorly operated wastewater treatments works, acid mine drainage, nutrients from agriculture, siltation of dams. A combination of these factors has led to high levels of water scarcity and an immense burden on the water supply. However, it must be noted that in 1994, South Africa (SA) embarked on developing numerous policies and strategies to address water challenges. While some levels of success have been achieved in terms of policy formulation, there is, however, a lack of comprehensive coordination and synergy that cut across the broad objectives of these policies in meeting environmental, social and economic targets and aspirations. Additionally, the implementation of the policies and programmes is stalled by structural, systemic and institutional factors, coupled with new challenges arising from climatic variabilities. Using a combination of qualitative and quantitative methods together with rapid appraisal of existing literature, we explore systemic and institutional factors impeding the implementation of policies and strategies designed to drive South Africa's water sector as envisaged within the National Development Plan of 2012. We argue that the water sector is faced with multifarious and interweaving challenges such as inadequate human capital, changes in climatic conditions, limited financial resources, infrastructural deficiencies largely linked to poor urban planning and rapid growth of informal settlements, rampant corruption and mismanagement, lack of stakeholders' involvement and compartmentalisation of institutions. This paper, therefore, recommends a community-based approach that enforces transparency and the participation of civil society, cross-sectoral cooperation and a broad range of stakeholders and decentralisation of policy implementation strategies.

Changing snow water storage in natural snow reservoirs

Abstract. This work introduces a novel snow metric, snow water storage (SwS), defined as the integrated area under the snow water equivalent (SWE) curve (units: length-time, e.g., m d). Unlike other widely used snow metrics that capture snow variables at a single point in time (e.g., maximum SWE) or describe temporal snow characteristics (e.g., length of snow season), SwS is applicable at numerous spatial and temporal scales. This flexibility in the SwS metric enables us to characterize the inherent reservoir function of snowpacks and quantify how this function has changed in recent decades. In this research, changes in the SwS metric are evaluated at point, gridded and aggregated scales across the conterminous United States (hereafter US), with a particular focus on 16 mountainous Environmental Protection Agency (EPA) Level III Ecoregions (ER3s). These ER3s account for 72 % of the annual SwS (SwSA) in the US, despite these ER3s only covering 16 % of the US land area. Since 1982, spatially variable changes in SwSA have been observed across the US with notable decreasing SwSA trends in the western US and in the 16 mountainous ER3s. All mountainous ER3 (except for the Northeastern Highlands in New England) exhibit decreasing trends in SwSA resulting in a 22 % overall decline in SwSA across mountainous ER3s. The peak monthly SwS (SwSM) occurs in March at all spatial scales, while the greatest percentage loss of SwSM occurs early in the snow season, particularly in November. Unsurprisingly, the highest elevations contribute most to SwSA in all mountain ranges, but the specific elevations that have experienced loss or gain in SwSA over the 39-year study period vary between mountain ranges. Comparisons of SwS with other snow metrics underscore the utility of SwS, providing insights into the natural reservoir function of snowpacks, irrespective of SWE curve variability or type (e.g., ephemeral, mountain, permanent). As we anticipate a future marked by increased climate variability and greater variability in mountain snowpacks, the spatial and temporal flexibility of snow metrics such as SwS may become increasingly valuable for monitoring and predicting snow water resources.

Quality evaluation of Nothofagus pumilio seeds linked to forest management and climatic events

Abstract Background Forest ecosystems undergo significant transformations due to harvesting and climate fluctuations, emphasizing the critical role of seeding in natural regeneration and long-term structural preservation. Climate change further amplifies these dynamics, affecting phenology across species and regions. In Tierra del Fuego (Argentina), Nothofagus pumilio (lenga) forests represent the most important timber resource, and it is managed through different silvicultural strategies. This species demonstrates notable post-disturbance regeneration, yet seed fall exhibits significant variability, leading to variations in seed quality (e.g., viability). This study aims to assess fluctuations in N. pumilio seed quality, determine how it varies concerning forest management strategies, annual productivity, and the co-occurrence of climatic phenomena including El Niño-Southern Oscillation (ENSO) and the Southern Annular Mode (SAM). Results Viable seeds represented 18.4% of the total, notably higher in unharvested than in managed areas. Conversely, empty seeds were more prevalent in harvested areas (> 75%). Seed quality exhibited significant differences across silvicultural treatments, except for insect-predated seeds, which had similar proportions across all areas, though dispersed retention showed higher predation. When considering years with varying production levels, high-production years favoured full and viable seeds, particularly in unharvested forests and aggregated retention, while low-production years saw reduced viability across all treatments. Quadratic models revealed that viability increased with seed production, where unharvested forests achieved the highest values. Climate variability influenced seed proportions, where ENSO+/SAM+ promoting more full and viable seeds, while ENSO–/SAM+ favoured non-predated seeds, especially in unharvested stands. Conclusions Seed quality varies among treatments and years with different levels of seeding. Variations in seed quality, linked to climatic events, influence seed viability. Seed quality plays a critical role in forest regeneration, ensuring a seedling bank for harvested stands to face climate variability. These findings are relevant for forest management and ecosystem services, considering the increasing climate variability and extreme events. Understanding these influences is crucial for Nothofagus pumilio forests' sustainability and global forest adaptation strategies.

Forest Cover and Locality Regulate Response of Watershed Discharge to Rainfall Variability in Caribbean Region

Reforestation often occurs when the economy shifts from agriculture to industry and services such as tourism. However, there is a lack of coherent knowledge and investigation about the impact of reforestation in the tropics on hydrological variability as well as flood risks. It is unclear how changes in forest cover and pattern will affect flood risks and watershed response to future altered rainfall intensity. This study uses the Soil Water Assessment Tool (SWAT+) to simulate the impact of reforestation, the locality of forest, and the concentrated rainfall on the hydrology of the largest watershed in Puerto Rico. SWAT+ is a computer model simulating watershed hydrology driven by meteorological input and the characteristics of soils and land use. We hypothesized that increased forest cover, especially at low elevation range, would reduce flood risk and that reduced rain days while maintaining the mean annual rainfall invariant would increase stream discharge variability. We found that reforestation significantly reduced large discharges but increased small discharges; that forest at low elevation tended to reduce large and extreme discharges in comparison with forest at high elevation; and that more concentrated rainfall not only increased the rainfall variability but also increased the discharge variability. However, both the impact of shifting forest locality and the response of watershed to altered rainfall intensity strongly depended on geophysical factors such as ranges of elevation and slope. Moving forests to lower elevation in subbasins with steeper slopes showed a stronger reduction in extreme discharges than in subbasins with flatter slopes. On the other hand, subbasins with steeper slopes tended to response more strongly to more concentrated rainfall with greater increase in discharge variability than subbasins with flatter slopes. To cope with future increased climate variability, our results favor reforestation at lower elevation for watershed with large elevation ranges and steep slopes.

Combined Effect of Freeze–Thaw Cycles and Biochar Addition on Soil Nitrogen Leaching Characteristics in Seasonally Frozen Farmland in Northeast China

Global climate warming and increased climate variability may increase the number of annual freeze–thaw cycles (FTCs) in temperate zones. The occurrence of more frequent FTCs is predicted to influence soil carbon and nitrogen cycles and increase nitrogen leaching. Biochar has the potential to increase soil organic carbon storage and decrease nitrogen leaching. This study aims to investigate the impact of freeze–thaw cycles (FTCs) on soil nitrogen leaching in temperate zones, considering the potential exacerbation of FTCs due to global climate warming and increased climate variability. This study focuses on how biochar, a carbon-rich material produced from biomass, might mitigate nitrogen leaching by influencing soil characteristics. This study explores the interactions between different laboratory-simulated FTC frequencies (ranging from 0 to 12 cycles) and various biochar addition ratios (0%, 2%, 4%, and 6% w/w) on soil nitrogen leaching based on a total of 60 soil columns. Pearson correlations between the soil quality indicators and nitrogen leaching characteristics were detected, and partial least squares path modeling (PLS-PM) was used to assess the effects of the FTCs, biochar addition ratios, and soil quality indicators on the nitrogen leaching content. The results showed that the amount of leached soil NH4+-N and NO3−-N reached 0.129–1.726 mg and 2.90–7.90 mg, respectively. NH4+-N and NO3−-N first increased and then decreased under the FTCs, with the highest values being observed after the 6th FTC. As the biochar addition ratio increased, the NH4+-N and NO3−-N contents decreased. Correlation analysis showed that the nitrogen leaching content was significantly related to the soil pH, soil organic matter (SOM), NH4+-N content, and microbial biomass carbon content (MBC) (p < 0.01). The results of the conceptual path model revealed that nitrogen leaching characteristics were significantly affected by the pH, SOM, soil nitrogen content, and biochar addition ratio. Our results suggest that biochar addition can help reduce nitrogen leaching in farmland soil in areas with black soil and seasonal freeze–thaw cycles.

The coincidence of climate extremes with sensitive crop growth phases: Projected impact on sustainable crop water use and crop yield in the IGB river basins

Increased climate variability and extremes are unequivocal with unprecedented impacts on water resources and agriculture production systems. However, little is known about the impacts of climate extremes at the intra-seasonal level which remained largely unexplored. We investigated the coincidence of climate extremes with sensitive crop growth phases of wheat and rice in the Indus, Ganges and Brahmaputra (IGB) river basins of South Asia. We also quantified the related impacts on irrigation water demand (IWD), gross primary production (GPP) and crop yields (CY) simulated by a hydrological-vegetation model (LPJmL) during 1981–2100 using RCP4.5-SSP1 and RCP8.5-SSP3 framework. The climate extremes revealed a higher frequency and intensity during crop growth phases with significant increasing trends in future. Diverse changes in IWD, GPP and CY are projected in future under the influence of crop phase-specific extremes. The crop phase-specific changes in the IWD of wheat and rice will intensify in the future. More than 50 % of the change in future wheat irrigation is caused by warm and dry extremes during the ripening phase. Whereas, increase in IWD for rice is mainly associated with warm extremes only. The crop phase-specific GPP shows a decreasing trend in future for both wheat and rice in the Western part of IGB with the largest decrease during the reproductive phase of wheat (up to 36 %) and vegetative phase of rice (>20 %). This decrease is clearly reflected in seasonal yields i.e., both wheat (20 %) and rice (12 %) showed a decrease in future linked with warm and dry extremes. However, in the Eastern part of IGB, the GPP will mostly increase in future during the three crop phases of wheat and rice. These results can be used to help develop efficient adaptation strategies considering seasonal changes and sensitive crop phases for sustained food and water security in South Asia.

Gendered livelihood impacts and responses to an invasive, transboundary weed in a rural Ethiopian community

Gender as unequal power relations intersects with global environmental change threatening agriculture-based livelihoods, including land degradation, increasing climate variability, and invasive alien plants. Commonly overlooked, invasive alien plants may have gendered impacts on everyday life that disproportionately affect the less powerful. Drawing on experiences of smallholder farmers in Ethiopia’s Oromia region with an invasive, transboundary weed, Parthenium hysterophorus L., this paper illustrates how environmental change interacts with pre-existing vulnerabilities to shape individual and household-level impacts and responses. We applied a feminist perspective in livelihoods and environmental change research and praxis to explore the intersection of gendered livelihoods and parthenium management in spaces of everyday life. While invasive plants, including parthenium, may be easily perceptible in the field, understanding impacts on livelihoods requires consideration of women’s and men’s roles and responsibilities within the broader household compound as well as intra-household decision-making. Parthenium can be harmful to environmental, animal, and human health, but unduly impacts women’s labor, spaces, and assets, including cows whose milk may be tainted by grazing in parthenium-infested fields. We demonstrate the importance of considering women’s social networks and so-called reproductive space and labor to understand gendered and place-based inequities of climate change. This study reveals intimate connections between environmental stressors and gendered livelihoods. Our findings demonstrate how inequalities can be reinforced by new forms of vulnerability, with response options socially differentiated. We argue that a feminist livelihood lens helps bridge the global scale of environmental change with local scales of gendered livelihood adaptation embedded within broader socio-environmental change.

Water-use characteristics of Syzygium antisepticum and Adinandra integerrima in a secondary forest of Khao Yai National Park in Thailand with implications for environmental management.

Southeast Asia has experienced widespread deforestation and change in land use. Consequently, many reforestation projects have been initiated in this region. However, it is imperative to carefully choose the tree species for planting, especially in light of the increasing climate variability and the potential alteration of plantation on the watershed water balance. Thus, the information regarding water-use characteristics of various tree species and sizes is critical in the tree species selection for reforestation. We estimated tree water use (T) of dominant species including Syzygium antisepticum and Adinandra integerrima, hereafter Sa and Ai, respectively, in a secondary tropical forest in Khao Yai National Park, Thailand, using sap flow data, and compared T between species and size classes. Additionally, we evaluated the responses of T of both species in each size class to environmental factors including soil moisture and vapor pressure deficit (VPD). Results showed consistently higher T in Sa compared to Ai across ranges of VPD and soil moisture. Under low soil moisture, T of Sa responded to VPD, following a saturating exponential pattern while Ai maintained T across different VPD levels, irrespective of tree size. No responses of T to VPD were observed in either species when soil water was moderate. When soil moisture was high, T of both species significantly increased and saturated at high VPD, albeit the responses were less sensitive in large trees. Our results imply that Ai may be suitable for reforestation in water-limited areas where droughts frequently occur to minimize reforestation impact on water availability to downstream ecosystems. In contrast, Sa should be planted in regions with abundant and reliable water resources. However, a mixed species plantation should be generally considered to increase forest resilience to increasing climate variation.

Revising the global biogeography of annual and perennial plants

There are two main life cycles in plants—annual and perennial1,2. These life cycles are associated with different traits that determine ecosystem function3,4. Although life cycles are textbook examples of plant adaptation to different environments, we lack comprehensive knowledge regarding their global distributional patterns. Here we assembled an extensive database of plant life cycle assignments of 235,000 plant species coupled with millions of georeferenced datapoints to map the worldwide biogeography of these plant species. We found that annual plants are half as common as initially thought5–8, accounting for only 6% of plant species. Our analyses indicate that annuals are favoured in hot and dry regions. However, a more accurate model shows that the prevalence of annual species is driven by temperature and precipitation in the driest quarter (rather than yearly means), explaining, for example, why some Mediterranean systems have more annuals than desert systems. Furthermore, this pattern remains consistent among different families, indicating convergent evolution. Finally, we demonstrate that increasing climate variability and anthropogenic disturbance increase annual favourability. Considering future climate change, we predict an increase in annual prevalence for 69% of the world’s ecoregions by 2060. Overall, our analyses raise concerns for ecosystem services provided by perennial plants, as ongoing changes are leading to a higher proportion of annual plants globally.

9 Practical Considerations for Adaptive Strategies By United States Grazing Land Managers with a Changing Climate

Abstract We outline practical considerations for grazing land adaptations with a changing climate, with an emphasis on the ranch operation scale and specific attention to directional climate changes and increased climate variability. These adaptive strategies fall into two themes: flexibility and learning under uncertainty. Ranches and livestock operations with greater land, social, or other capital resources may have more flexibility. Risk can be reduced for managers (ranchers, farmers, operators, and livestock managers) through participation in conservation or farm policy programs and/or market-based approaches. Bolstering adaptive capacity across landscapes and time can originate from social capital of operators and strategic collaborations among managers and scientists. As climate diverges from historical baselines and the realm of managers’ experiential knowledge, new conceptual frameworks are needed to structure conversations, influence research relevancy and impact, and drive imaginative solutions among researchers, managers, and local communities for socio-ecological systems. We provide simplified frameworks to help guide conversation, future research, and new imaginative solutions for systems-scale knowledge needs and adaptation to address increasingly uncertain and complex change at multiple scales. Practical considerations for adaptive strategies by grazing land managers with a changing climate will be accelerated through 1) collaborative efforts among managers and explicitly with science-management partnerships becoming more mainstream, 2) co-produced research with managers and researchers at ranch-scales, 3) development of communities of practice and associated learning opportunities, and 4) continued co-development and advancement of technologies and tools that result in high uptake adoption by ranch managers.

8 Impacts of Future Climate Scenarios on the Beef Industry of the Great Plains and Western Us

Abstract Global average temperatures have increased by 1.1 degrees Celsius compared with pre-Industrial times and future temperature increases will be driven by anthropogenic greenhouse gas emissions trends. Impacts of climate change vary by geographic regions, with the Great Plains and Western US likely to experience increased temperatures, increased frequency of drought, and more extreme precipitation events. These climate impacts can affect the beef industry in those regions in multiple ways from increasing heat stress, decreasing forage availability, impacting forage quality, and reducing water availability for drinking water and feed production. In the southwestern US, increasing temperatures are likely to increase evapotranspiration, reduce snow cover, and lead to earlier snow melts, all of which can contribute to the aridification of the region. For cow-calf production within the region, aridification will reduce the forage biomass available for grazing cattle operations and reduce carrying capacity, creating potential vulnerabilities to rangeland ecosystems and rural communities dependent upon the cattle industry. Increased incidence of heat waves in the Great Plains and Western US can negatively impact vulnerable cattle populations, such as finishing cattle, particularly those housed in environments with minimal heat stress mitigation measures. Decreased water availability can potentially shift cattle production and feed production away from arid regions dependent upon vulnerable water resources, such as the Colorado River and Ogallala aquifer. In general, the increased climate variability and aridification of some parts of the Great Plains and Western US will create risks for the beef industry that will likely necessitate changes, from shifting cattle population to increased use of heat stress mitigation strategies.

315 Implementation of Large-Scale Climate-Smart Agriculture Practices and Research on Beef and Bison Grazing Lands

Abstract Today’s livestock producers face increasing public scrutiny because animal agriculture is often cited as a major contributor to greenhouse gas (GHG) emissions. However, this negative perception does not take into account the carbon (C) sequestration benefits of grazing livestock nor that grazing lands account for 25% of the global soil sequestration potential of soil C storage. Grazing beef cattle and bison are key to healthy grassland ecosystems and provide the most nutrient dense source of protein available for human consumption. Beef and bison producers who graze their livestock are widely recognized as environmental stewards because they use sustainable grazing practices that maintain grassland health. These practices are considered climate-smart agriculture (CSA) because they promote soil C sequestration and resilience to increased climate variability. Yet, these same producers are generally overlooked in GHG reduction and C sequestration incentives because of a relative lack of cost-effective methods to measure C and GHG sinks and sources. Emerging technologies are beginning to bridge that gap by paving the way to develop, implement, and monitor CSA practices. Furthermore, rangelands in the U.S. dedicated to supporting forage-based livestock production amount to nearly 940 million acres. This is more than double the acres dedicated to row crops and represents enormous potential to contribute to U.S. climate change commitments. Successful implementation and monitoring of CSA land management practices creates potential to develop climate-smart livestock commodities that sustainably provide economic incentives to producers operating resilient livestock grazing systems. Recently, South Dakota State University, along with ten external partners, was awarded a CSA commodity development grant by the USDA and NRCS focused on CSA-raised grazing beef cattle and bison in the Northern Great Plains. Specific objectives include: 1) developing and implementing existing and novel CSA practices alongside custom grazing plans; 2) measuring, monitoring, reporting, and verifying CSA practice impacts on GHG emissions, C sequestration, and ecosystem biodiversity of plants, arthropods, and wildlife; and 3) creating sustainable, value-added market opportunities for producers using CSA practices. To achieve these objectives, the project team is partnering with producers throughout the Northern Great Plains and beyond and will provide incentives for CSA practice implementation. Additionally, emerging and novel technologies will be used to collect large-scale data across producer operations and test sites to determine and refine GHG and C sequestration estimates associated with range beef cattle and bison systems. The long-term goal of this project is to provide CSA beef and bison producers with sustainable, value-added market opportunities that align with consumer preferences and demand.

302 Incremental Variables in Predicting Beef Cattle Dry Matter Intake

Abstract The great strain of increasing climate variability on animal agriculture necessitates improvement of current production processes, the development of methods to measure individual feed and water intakes, and the improvement of feed and water use efficiency in cattle. The use of machine learning (ML) approaches in predicting beef cattle dry matter intake (DMI) have provided groundwork for improvement of beef cattle production using big data and ML. However, despite wide variation between daily feed intakes, typical variables in animal intake-based ML approaches are not incremental, not allowing for daily prediction of intake. Our work introduces first-differenced intake, climate, and animal performance variables into a ML algorithm to predict beef cattle DMI and increase the immediacy of prediction applications. A total of 745 animals were evaluated in eight test groups from 11/25/2019 to 9/2/2021 in a dry lot equipped with In-Pen Weighing Positions and Feed and Water-Intake Nodes. Relationships among average daily gain (ADG), DMI, residual feed intake (RFI), water intake (WI), residual water intake (RWI), animal performance variables, and environmental variables at the individual animal level were investigated on a first test group of 125 Angus bulls and 53 crossbred steers. Out-Of-Bag root mean square error (OOB RMSE), an internal measure of Random Forest (RF) prediction accuracy, was used as a measure of error between model-predicted and observed DMI. Input variables were first-differenced by differencing a variable’s value between sequential test days for the entire test period. Two models were run using the RF package in R (ntree = 500, mtry = 11), with the first model (M1) using a standard test-train data split and the second model (M2) using all first-differenced and non-incremental observations to train the model. The model incorporating the test-train split performed marginally better than M2 (OOB RMSE = 1.39 and 1.44, respectively), indicating that first-differenced input variables can be used to predict daily individual DMI by within 1.39 kg by using M1. Using percent-increase in MSE (%IncMSE), first-differenced variables were found to be of less overall predictive value than non-incremental variables, with incremental daily gain and first-differenced water intake being ~55 and 45% less predictive than ADG and overall water intake in both M1 and M2. Though first-differenced variables were less predictive than non-incremental variables, inclusion of first-differenced variables allowed for prediction of individual DMI by within 1.39 kg. Our work demonstrates critical preliminary steps in the development of a deployable algorithm for the efficient prediction of DMI and the improvement of beef cattle intake efficiencies for the continued sustainability of animal agriculture.

Cereal drought adaptation strategies

Water stress prevents all cropping systems from reaching their production potential. This stress is likely to be amplified by increased climate variability. Cereals, food crops and staple foods for most of the world's population are significantly affected by drought. By 2050, grain production must increase by about 70% to meet global food needs. However, current studies of adaptive strategies to mitigate the effects of water stress remain limited. Varietal adaptation and the development of new ones, as well as the adoption of appropriate cropping practices, are among the solutions being considered. To reinforce and support these approaches, new ecological and natural methods, including the use of biostimulants, could be adopted for efficient management of production systems and to limit yield losses under stress conditions. In this context, this review focuses on the main cereal adaptation strategies to drought.

Does climate information source matter in smallholder farmers' climate resilience? Comparative insights from Malawi and Ghana

Due to increasing climate variability and change, the need for more accessible, timely, and reliable climate information has risen, particularly in African rain-fed smallholder farming communities. Yet, studies on the role of information sources in climate resilience are limited. Given the plurality of climate information sources, it is uncertain which medium offers better chances to build resilience against the changing climate. To fill this gap, we employed quantitative survey data from smallholder agricultural households in the Mzimba District in Malawi (n = 1090) and the Upper West Region of Ghana (n = 1100). Our findings reveal that in Malawi, households whose primary source of climate information was the mass media (OR = 2.37; p ≤ 0.001) and external organizations (government, private sector, and nonprofit sector) (OR = 2.11; p ≤ 0.001) were over two times more likely to rate their resilience as good compared to those who relied primarily on self-experience. While in Ghana, interpersonal sources (other farmers, friends/relatives, special activities by the community) significantly increased a household's odds (OR = 3.46; p ≤ 0.001) of reporting good resilience, while external sources reduced farmers' likelihood of reporting climate resilience (OR = 0.06; p ≤ 0.001) compared to those who relied primarily on self-experience. Farmers in Malawi who practiced intercropping were also more likely to rate their resilience as good than those engaged in monocropping. The findings suggest that the relevance of information sources on climate change resilience is place-specific and that some sources may impede resilience-building if contextual factors are sidelined. This finding reaffirms the need for context-specific policies due to the heterogeneity of agrarian communities across Africa.

Effects of climate variability changes on runoff and erosion in the Western European Loess Belt region (NW, France)

Runoff and soil erosion are very pronounced in the Western European Loess Belt. In this study, the distributed physically-based model CLiDE is calibrated, validated, and applied to a catchment of this area (Dun, NW, France) to assess the hydro-sedimentary impacts of climate change scenarios. Despite considerable progress over the last decade in the study of runoff and soil erosion in the context of climate change, the effects of changes in the temporal variability of precipitation remain poorly understood, especially at the scale of a river basin. To examine these relationships more closely, we developed a stochastic weather generator to individually adjust the components that structure the temporal variability of rainfall. The climate scenarios considered represent projections to the year 2100 of the temporal variability of rainfall over NW Europe. The scenarios are based on historical daily rainfall records (1990–2012) and 4 exploratory assumptions: a 50 % decrease in the interannual rainfall regime (scenario 6yD), a 100 % increase in the interannual rainfall regime (scenario 6yI), a 50 % increase in the seasonal rainfall regime (scenario 1yI) and a 50 % increase in the synoptic rainfall regime (scenario 3dI). Simulated daily water and sediment discharges and erosion/deposition maps for each scenario are compared to those simulated for the situation without changes in rainfall. The time series were aggregated over different time intervals to allow for a multi-scale analysis of the differences. The results indicate that the model provides a satisfactory prediction of the catchment's water and sediment discharges, especially over the calibration period. Increased climate variability, whether on a synoptic (3dI), seasonal (1yI) or interannual (6yI) scale, leads to increased runoff and erosion. Increasing the synoptic rainfall variability (3dI) leads to the largest increase in mean annual runoff and erosion. Only the reduction of the interannual rainfall variability (6yD) provokes the decrease of these values.

Weather-Informed Recommendations for Pest and Disease Management in the Cashew Production Zone of Côte d’Ivoire

Poorly informed pest and disease management strategies can have detrimental effects on the environment, crop quality, crop yield, farmers’ income, and the overall sustainability of agriculture. For this reason, integrated pest and disease management (IPDM) draws on knowledge from various research fields to effectively manage risks of bio-aggressor outbreaks. However, many agricultural sectors of Sub-Saharan African countries lack such necessary knowledge, including the epidemiology of bio-aggressors in relation to the increased climate variability. The objective of this work is to provide weather-based guidance for the development of sustainable pest and disease control strategies in cashew cultivation areas of Côte d’Ivoire, the second most important cash crop of the country. Leveraging the bioclimatic knowledge in the literature about fungi and insects, we explored four-year hourly data (2017–2020) of 34 sites of the cashew production zone. The outputs showed potentially conducive weather events for fungi and insects throughout the entire cashew production areas, with the forest–savanna transition zone being the most critical. These outputs were used to elicit recommendations for pest and disease management in consultation with a multidisciplinary stakeholder task force. They recommended that effort for disease prevention in the forest–savanna transition zone, the new cashew production zone, should be an incrementation of the one already recommended in the north savanna. Weather-based disease monitoring, entomopathogenic-fungi-based pest control, and the promotion of early-maturing cashew genotypes are also recommended, especially in the forest–savanna transition zone.