Climate Change Information Research Articles

Exposure to Climate Change Information on Affect and Pro-Environmental Behavioural Intentions: A Randomised Controlled Trial

Climate change and its impact are being acknowledged through extensive media coverage. Knowledge gaps between mental health and climate change have been highlighted, which is an increasingly prevalent issue. Furthermore, mental health impacts such as climate anxiety and its implications on behaviour remain unclear. The study aimed to investigate the effect of climate change exposure on affect and pro-environmental behavioural intentions in a randomised controlled trial. An online survey was completed by 100 adult participants and included measures of affect and pro-environmental behavioural intentions pre- and post-exposure. Participants were randomly allocated to a group that saw a climate change video (n = 55) or a group that saw a non-climate change video (n = 45). The findings were that participants in the climate change group showed a significant increase in negative affect and pro-environmental behavioural intention scores post-video exposure compared to the non-climate change video group. This suggests that climate change video exposure negatively influences affect but also potentially increases the intention to act pro-environmentally. These findings have the potential to support policies and societal change; however, further investigation into the type of contents, actual behaviour change, and impacts on diverse populations (e.g., minority groups) is needed.

Linking Climate Change Information with Crop Growing Seasons in the Northwest Ethiopian Highlands

In Ethiopia, the impacts of climate change are expected to have significant consequences for agriculture and food security. This study investigates both past (1981–2010) and future (2041–2070) climate trends and their influence on the length of the growing season (LGS) in the North-Western Ethiopian highlands. Climate observations were obtained from the National Meteorological Agency of Ethiopia, while the best performing and highest resolution models from the CMIP5 experiment and RCP6 (Coupled Models Intercomparison Project and representative concentration pathway 6) were used for the analysis. Standard statistical methods were applied to compute soil water content, evaluate climate variability and trends, and assess their impact on the length of the growing season. Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show that the region has experienced cooler years than hotter years in the past. However, in the future, the coolest years are expected to decrease by −1.2 °C, while the hottest years will increase by +1.3 °C. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to receive similar rainfall in the future. On the other hand, the rainfall amount in the season February to May (FMAM) is expected to assist only with early planting. For the season October to January (ONDJ), the rainfall amount may help lengthen the growing season of JJAS if properly utilized; otherwise, the season has the potential to destroy crops before and during the harvesting time. The soil water content changes in the future remain close to those of the past period. The length of growing seasons has less variable onset and cessation dates, while in the future, the length of the growing period (LGP) of 174 to 177 days will be suitable for short- and long-cycle crops, as well as double cropping, benefiting crop production yield in the North-Western Ethiopian highlands in the future.

Shaping climate change discourse: the nexus between political media landscape and recommendation systems in social networks

Recommendation systems have become ubiquitous, and they actively participate in creating our individual and collective identity. In this paper, the diffusion of climate change information has been studied based on YouTube’s recommendation system and the political media landscape. The YouTube channels of CNN, BBC News and Fox News, as the most popular channels, respectively, for Left, Center and Right parties, were explored using web scraping and social network analysis to check what kind of recommended content will pop up if a user looks for climate change videos. Using an agent-based modeling approach, the competition between Left, Center and Right media in pushing their own narrative of climate change in society was simulated. The results suggest YouTube’s recommendation algorithm is highly biased since most of the recommended content was from the same channel fitting their own political agenda. The agent-based modeling indicates the size of a network is a decisive factor in further spread of a message as Left media always dominated Center and Right media in pushing their own perspective on climate change regardless of higher weights assigned to Right media. This study shed light on how public perception on climate change can be shaped by recommendation systems and digital companies.

Climate Change Risks Disclosure: Do Business Strategy and Management Characteristics Matter?

This research aims to broaden the understanding of the determinants of climate change disclosure, where the study analyzes the impact of corporate business strategy and Chief Executive Officer (CEO) overconfidence on the level of climate change disclosure. The study followed a mixed-methods approach that combines quantitative and qualitative techniques to comprehensively examine the relationships used by the content analysis method to analyze the annual reports of a sample of Saudi companies for the period from 2019 to 2022 to measure the level of disclosure of practices related to climate change. The results of the study show that the companies that tend to adopt the initiative strategy provide more information about climate change than the defending companies do, while the CEO’s overconfidence does not affect the level of climate change disclosure. The results of the study indicate that the nature of the strategic direction adopted by the company is more important in determining the motives for disclosing climate change information than the personal characteristics of management.

Dynamic and Thermodynamic Contributions to Late 21st Century Projected Rainfall Change in the Congo Basin: Impact of a Regional Climate Model’s Formulation

Addressing the impacts of climate change requires, first of all, understanding the mechanisms driving changes, especially at the regional scale. In particular, policymakers and other stakeholders need physically robust climate change information to drive societal responses to a changing climate. This study analyses late 21st-century (2071–2100) precipitation projections for the Congo Basin under representative concentration pathway (RCP) 8.5, using the Rossby Centre Regional Climate Model (RCM) RCA4. Specifically, we examine the impact of the RCM formulation (reduction of turbulent mixing) on future change in seasonal mean precipitation by comparing the results of the modified model version (RCA4-v4) with those of the standard version (RCA4-v1) used in CORDEX (Coordinated Regional Climate Downscaling Experiment). The two RCM versions are driven by two global climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5). The results show that seasonal precipitation is largely affected by modifications in the atmospheric column moisture convergence or divergence, and, in turn, associated with changes in the dynamic (ΔDY) and thermodynamic (ΔTH) components of the moisture-budget equation. Projected decreased precipitation in the dry seasons (December–January–February and June–July–August) is linked to increased moisture divergence driven by dynamic effects (changes in circulation), with most experiments showing ΔDY as the main contributor (>60%) to the total moisture budget. Overall, precipitation is projected to increase in the wet seasons (March–April–May and September–October–November), which can be attributed to both dynamic and thermodynamic effects, but with a larger thermodynamic contribution (changes in specific humidity, ΔTH > 45%), compared to the dynamic one (ΔDY > 40%). Through a comparison of the two model versions, we found that the formulation (reducing turbulent mixing) and boundary conditions (driving GCM) strongly influence precipitation projections. This result holds substantial value for ensuring the fitness of models for future projections intended for decision-makers.

Cloud-Type Classification for Southeast China Based on Geostationary Orbit EO Datasets and the LighGBM Model

The study of clouds and their characteristics provides important information for understanding climate change and its impacts as it provides information on weather conditions and forecasting. In this study, Earth observation (EO) data from the FY4A AGRI and Himawari-8 CLP products were used to classify and identify distinct cloud types in southeastern China. To reduce the impact of parallax between geostationary satellites, we proposed adopting a sliding detection method for quality control of cloud-type data. Additionally, the Bayesian optimization method was employed herein to tune the hyperparameters of the LightGBM model. Our study results demonstrated that Bayesian optimization significantly increased model performance, resulting in successful cloud-type classification and identification. The simultaneous use of visible and shortwave infrared channels, and brightness temperature difference channels, enhanced the model’s classification performance. Those channels accounted for 43.79% and 21.84% of the overall features, respectively. Certainly, the model in this study outperformed compared with the traditional thresholding method (TT), support vector machine (SVM), and random forest (RF). Results showed a model prediction accuracy of 97.54%, which was higher than that of TT (51.06%), SVM (96.47%), and RF (97.49%). Additionally, the Kappa coefficient of the model was 0.951, indicating the model’s classification results were consistent with the true values. Notably, this performance also surpassed TT (0.351), SVM (0.929), and RF (0.950).

How green credit affects corporate environmental information disclosure: evidence from new energy listed companies in China

IntroductionEnvironmental information disclosure is an important means to protect the ecological environment, and global climate change puts forward higher requirements for corporate environmental information disclosure. New energy companies play an important role in addressing climate change and environmental information disclosure, and should strengthen environmental information disclosure and actively participate in ecological environmental protection.MethodsThis paper selected Chinese new energy listed companies as the research sample to investigate the impact of green credit on corporate environmental information disclosure, and proposed and empirically tested the hypothesis on the mechanism of the effect of green credit on environmental information disclosure.ResultsThe regression results indicated that green credit can effectively improve the quality of corporate environmental information disclosure, and this conclusion is still significantly valid after robustness test; The impact mechanism tests showed that green credit can change the level of corporate environmental information disclosure by controlling company size. This paper also tested the heterogeneity and adjustment effects, showing that the relationship between green credit and environmental information disclosure are affected by multiple factors.DiscussionsCombining the research of this paper and previous research results, it is found that the positive impact of green credit on corporate environmental information disclosure has been confirmed by academic research and practical verification. However, the implementation effect of green credit policy will be affected by the economic level, regional differences, and the comprehensive impact from companies, financial institutions and government departments.

What are Farmer Household Coping Strategies for Facing Crop Loss: Evidence from Indonesia


 
 
 The climate change that has occurred in the last decade has seriously impacted food availability and price pressures from the macro side, as well as the sustainability of farming activities and the welfare of farmers from the micro side. One form of climate change is crop failure; thus, to anticipate crop failure, farming households implement coping strategies to survive well. This study aimed to analyse the coping strategies used by farm households to deal with crop failures. The data used in this study were sourced from the Indonesian Family Life Survey (IFLS) conducted in 2007 and 2014. There were 3338 samples of farming households in a panel data format that could be used in the analysis. The analytical method used in this study uses a fixed effects approach at the household and rural levels to avoid potential bias from endogeneity and heterogeneity problems. The results showed that the coping strategies adopted by farming households were more likely to sell livestock and household assets and increase the number and frequency of loans. Reducing consumption has not been statistically proven as a coping strategy chosen by farming households facing crop failure.
 
 

Abstract A113: Attitudes towards climate change among cancer patients and caregivers in Puerto Rico

Abstract Introduction: Climate Change is a significant public health problem. Cancer survivors are among the most vulnerable populations during extreme weather events. In this research we aimed to describe attitudes towards climate change among a Hispanics population of cancer patients and caregivers. Methods: A cross-sectional study was done among adults ≥21 years old living in Puerto Rico (PR). Data collection started on April 2023 and is ongoing. After informed consent, participants completed an online or printed survey including sociodemographic, clinical and climate change-related variables. Participants were recruited through activities aimed at cancer patients/survivors and caregivers in PR, cancer treatment and accommodation centers, social media and tv. Descriptive statistics and bivariate analysis were used to describe the outcomes of interest, overall and by type of participant (patient/caregiver). Logistic regression models used to assess demographic factors associated to individual attitudes. Results: From April 22nd-June 8th, 2023, the study has recruited 318 participants from 66 municipalities in PR. For patients, mean age is 56.3 years ±13.5 SD, 79.1% are women, and 85.4% have more than high-school education. For caregivers, mean age is 45.3 years ±15.4 SD, 91.4% are women, and 92.7% have more than high-school education. Most participants agreed that climate change information is important to them (98.1%), 50.2% disagreed that climate change is inevitable and 90.2% disagreed that it is too early to tell whether climate change is really a problem. Meanwhile, 96.0% agreed that as an individual, they can influence climate change and 80.1% agreed that the government should reward the people who contribute to mitigating climate change. Furthermore, 83.3% agreed that investing in technological innovations is required to tackle climate change. Meanwhile, most participants believe that each individual (98.4%) as well as the government (99.0%) must take action to help reduce the impact of climate change on the population. Finally, 17.3% agreed that they worked to make a living, even if it is to the environment’s detriment and 27.8% agreed that people have the right to change the environment to suit their own needs. Multivariate logistic regression models showed that individuals with more than high-school education were more likely to agree to be working to make a living, even if it is in the environment detriments (OR=2.94, 95% CI=1.19-7.25) and to agree that people have the right to change the environment to suit their own needs (OR=2.21, 95% CI=1.07-4.60) as compared to their counterparts. No differences were observed between patients and caregivers. Conclusions: This Hispanic population of patients and caregivers is concerned about climate change, is mostly interested in mitigating its effects and thinks that the government should be involved in these efforts. This information is important for cancer control plans and for interventions that target climate change and its impact on cancer populations. Citation Format: Ana P. Ortiz, Fabiola A. Rivera-Gastón, Jimena Pérez, Pablo A. Méndez-Lázaro. Attitudes towards climate change among cancer patients and caregivers in Puerto Rico [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A113.

Participatory Communication to Strengthen Farmers' Empowerment and Adaptation in Facing the Impacts of Climate Change

Agriculture and farmers are sectors and parties affected by climate change. Unfortunately, farmers' knowledge and adaptive capacity are still low due to the limited climate change information that they receive. The development of communication models to strengthen the interaction and flow of information has been very active. However, it has not yet addressed the lack of empowerment and scarcity of farmer participation. Therefore, we need a dialogical, horizontal, participatory communication model with an emphasis on empowerment and farmer participation. This research, using a participatory communication model, aims to see how participatory communication can encourage the empowerment and adaptability of farmers to climate change. This study uses a participatory action research approach with participatory data collection techniques for the Rural Communications Assessment (PRCA). The theory used is participatory communication and social change, which allows farmers and researchers to be equally involved and dialogue to occur. This research demonstrates the fact that participatory communication through a dialogue process can promote common goals and action in dealing with climate change. In addition, this research was also able to increase farmer empowerment, which was marked by changes at the individual farmer and social levels. These changes take the form of strengthening farmers' knowledge, perceptions, and skills related to climate change and adaptation actions and increasing farmer participation in village development planning. Farmers have been able to push the issue of strengthening farmer resilience to become part of the village development plan.

The impact of climate change on water resources and food security in Indonesia

The agricultural industry in Indonesia is facing a significant challenge in the form of climate change, particularly with regards to its impact on water resources. Climate change has various consequences, such as diminished precipitation, compromised water quality, and alterations in water availability. These outcomes pose significant risks to both food security and the long-term viability of agricultural output. The vulnerability of the water sector on Java Island is further intensified by factors such as population growth, land use changes, excessive utilization of water resources, and the expansion of infrastructure. The phenomenon of diminishing water discharge and alterations in water quality has emerged, posing a risk to water resources and substantial reservoirs. There is a pressing need for enhanced comprehension and proactive measures to effectively mitigate the repercussions of climate change on Indonesia's water resources.

Agroforestry As An Alternative To Facing Climate Change In The Community, Ponorogo Regency

Changes in the seasons on earth can cause problems for farmers in determining the planting and harvesting seasons. Management of forest areas with good agroforestry strategy by utilizing it to produce food in partnership with the community effectively inhibits the increasing rate of climate change. The agroforestry implementation strategy with the social and economic conditions of the community is also used to explore how far the impact of climate change on changes in current conditions. . The research aims to formulate strategies that must be developed to adapt to climate change. The AHP results show that the economic aspect has a priority weight of 0.89, the environmental factor has a 0.39 weight and the organizational part has a 0.26 weight. Work steps of the parties involved and priorities in the short and long term. For the parties involved, it is necessary to prioritize its implementation so that the community's economy can run according to expectations. The short-term priorities are training on climate change information and its impacts, group management and administration, entrepreneurship, marketing, and intensive mapping of CSR opportunities. In the long term, the government, academic can provide facilitators and assistance for technology transfer in dealing with climate change.

Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1

Abstract. The Canadian Earth System Model version 5.0 (CanESM5.0), the most recent major version of the global climate model developed at the Canadian Centre for Climate Modelling and Analysis (CCCma) at Environment and Climate Change Canada (ECCC), has been used extensively in climate research and for providing future climate projections in the context of climate services. Previous studies have shown that CanESM5.0 performs well compared to other models and have revealed several model biases. To address these biases, the CCCma has recently initiated the “Analysis for Development” (A4D) activity, a coordinated analysis activity in support of CanESM development. Here we describe the goals and organization of this effort and introduce two variants (“p1” and “p2”) of a new CanESM version, CanESM5.1, which features important improvements as a result of the A4D activity. These improvements include the elimination of spurious stratospheric temperature spikes and an improved simulation of tropospheric dust. Other climate aspects of the p1 variant of CanESM5.1 are similar to those of CanESM5.0, while the p2 variant of CanESM5.1 features reduced equilibrium climate sensitivity and improved El Niño–Southern Oscillation (ENSO) variability as a result of intentional tuning of the atmospheric component. The A4D activity has also led to the improved understanding of other notable CanESM5.0 and CanESM5.1 biases, including the overestimation of North Atlantic sea ice, a cold bias over sea ice, biases in the stratospheric circulation and a cold bias over the Himalayas. It provides a potential framework for the broader climate community to contribute to CanESM development, which will facilitate further model improvements and ultimately lead to improved climate change information.

Exposure to climate change information predicts public support for solar geoengineering in Singapore and the United States

Solar geoengineering is a controversial climate policy measure that could lower global temperature by increasing the amount of light reflected by the Earth. As scientists and policymakers increasingly consider this idea, an understanding of the level and drivers of public support for its research and potential deployment will be key. This study focuses on the role of climate change information in public support for research and deployment of stratospheric aerosol injection (SAI) in Singapore (n = 503) and the United States (n = 505). Findings were consistent with the idea that exposure to information underlies support for research and deployment. That finding was stronger in the United States, where climate change is a more contentious issue, than in Singapore. Cost concern was negatively related to support for funding and perceived risk was negatively related to support for deployment. Perceived government efficacy was a more positive predictor of support for funding in Singapore than in the United States. Additionally, relatively low support for local deployment was consistent with a NIMBY mindset. This was the first study to quantify the role of climate change information in SAI policy support, which has practical implications for using the media and interpersonal channels to communicate about SAI policy measures.

An overview of Climate Change Impacts on the Health Sector for the Research Program of the National Adaptation Plan Support Project in Senegal

Senegal, a coastal country in the semi-arid Sahel region, faces significant risks associated with climate variability and climate change. Climate change is already affecting vulnerable people’s wellbeing and it’s expected to contribute to the (re)emergence of vector-borne, some water-borne and heat-related diseases, which will have disastrous consequences on the country’s fragile health system and socio-economically vulnerable population. Our contribution to the National Adaptation Plan support Project - Global Environment Fund (NAP-GEF) aims to support community- based epidemiological surveillance and the design/maintenance of health information systems in order to improve planning, decision-making, and public health response. Our methodological approach aims to build a detailed climate and health database to describe the spatio-temporal characteristics of the climate-health relationships at national scale. Considering various indices of targeted diseases, we assess the degree of transmission of those diseases in Senegal for different historical period (1950-2014 and projections (2015-2100) based on a combination of the Shared Socio-Economic Pathways (SSPs) produced within the Coupled Model Intercomparison Project, phase 6 (CMIP6). Selected diseases include malaria, meningitis, dengue and Chronic – non communicable to heat waves. The project will strengthen institutional capacity to mainstream climate related risks within the Ministry of Health’s strategies and governance model, enabling a public health system framework to support long-term and sustainable adaptation funding and programs. The project is being implemented jointly with the Ministry of Environment and Sustainable Development (MEDD) and the Ministry of Health and Social Action (MSAS). The findings in the project will guide and operationalize community-based early-warning systems and adaptation strategies specific to local climate-sensitive diseases in targeted regions in Senegal, which will feed into the national health prevention, response, and care strategies adapted to the needs of local communities. Development of scientific evidence and a knowledge management system get started in this study about the links between climate change and health through the launch of studies in collaboration with research institutions. However, barriers or limitations to integrating climate change data and information into health policies have also been identified

From the classroom to the farm: a lesson plan that promotes smallholder farmers' education and training about plant pathology in the context of climate change.

Climate change represents one of the biggest threats to agricultural productivity around the world. In the tropics, extreme climate and pest and disease outbreaks represent one of the biggest climate change threats to smallholder farmers. Understanding smallholder farmers' educational needs and increasing access to information and awareness of climate change through education and training are key first steps to enhance the adaptive capacity of smallholder farmers. In a primary effort to increase accessible training and education to these communities, we developed a plant pathology lesson plan. The lesson plan introduces basic concepts in plant pathology and disease management using diverse educational activities focused on experiential and collaborative learning. This lesson plan may have implications in enhancing farmers' adaptive capacity and increasing accessible education to underrepresented farming communities around the world.

Understanding factors intercepting response of rice farmers to climate change in Ebonyi State, Nigeria

<p>Understanding factors intercepting the response of rice farmers to climate change in Ebonyi State, Nigeria, was investigated. A total of 70 rice farmers were sampled using a multi-stage sampling technique and administered a questionnaire. Primary data was collected and analyzed using descriptive statistics (mean, frequency, percentage, chart) and an ordinary least squares multiple regression model. Results show that the rice farmers cultivated on small land holdings, were relatively educated, sourced their land via inheritance, and had 16 years of farming experience. Results reveal that 72% of the rice farmers are highly aware of climate change, while 17% and 11% are relatively aware and not aware, respectively. Temperatures, rainfall, and the number of rainy days have positive effects on rice production, while sunshine hours and relative humidity have negative effects on rice production. Age, gender, education, farm size, extension contacts, and participation in workshops were significant variables influencing rice production in the state. Capital, crude implements, pests and diseases, poor soil, lack of incentives, and cultivation systems were the non-climatic factors that influenced rice cultivation in the state. Farmers were recommended to embrace climate-smart cropping systems and seek early climate change information to mitigate the adverse effects of climate change on rice cultivation.</p>

Study on the Impact of Climate Change Information Sources on Farmers’ Decisions on Adaptive Farming Behavior: Based on 1200 Questionnaires in Shaanxi Province, China

Study on the Impact of Climate Change Information Sources on Farmers’ Decisions on Adaptive Farming Behavior: Based on 1200 Questionnaires in Shaanxi Province, China

Climate Change and Sweet Potato Production; Empirical Insights from Ebonyi State, Nigeria

Climate change poses significant challenges to agriculture and land productivity particularly in regions heavily dependent on rain-fed agriculture like Ebonyi State, Nigeria. This study analyzed the effects of climate change on sweet potato production in Nigeria. Multi-stage sampling procedure was used to select 301 respondents. The drafted questionnaire was used for data collection following the specific objectives of study. Descriptive statistics, land productivity model, and multiple regression model were used for the data analysis. Results revealed that the majority of respondents (64.1%) were males, married (73.1%), young (42.2%), experienced (55.5%) and relatively educated (49.8%) with household and farm sizes of 7 and 1.8 hectares. The majority of the farmers (41.5%) were aware of changes in climate. Farm sizes of 1.1-2.0 hectares produced the highest land productivity (1769.831 hectares) in the state from about 51.5% of the farmers. Rising temperature, rainfall, and number of rainy days, influenced sweet potato production negatively; while sunshine hours and relative humidity had significant positive influences. Poor access to extension and services, land fragmentation, capital, inadequate information concerning climate change, and high cost of input resources constrained potato cultivation. The study recommends farmers to practice climate smart agricultural techniques and to seek early climate change information to mitigate negative effects of changing climate on sweet potato production.

Climate change information tailored to the agricultural sector in Central Europe, exemplified on the region of Lower Franconia

There is a growing societal, economic, and political demand to translate available data on regional climate change into sector-specific, practice-oriented, and user-friendly information. The study presents a demand-driven approach to specify the impacts of regional climate change on agriculture, viticulture, and fruit and vegetable growing in Lower Franconia, southern Germany, a region with heterogeneous topography, diversified land use patterns, and intense activities in the sectors specified above. The approach is based on an ensemble of high-resolution regional climate model projections, a bias correction tool, and a large spectrum of meteorological (extreme) indicators that are crucial to the agricultural sector in Central Europe, as inferred from a stakeholder survey.For several decades, Lower Franconia represents a hotspot region of climate change with enhanced heat waves, prolonged droughts, and intermittent local flooding by heavy rainfall events. Results of the high-resolution regional climate model projections indicate an increase of hot days and tropical nights by a factor of 5 and 12, respectively, if greenhouse gas emissions continue to grow until 2100 according to the RCP8.5 emission scenario. At the same time, droughts will occur more frequently and last longer while rainfall intensity enhances. A longer growing period starting more than 40 days earlier (compared to the reference period 1970 to 1999) implies a higher risk of late frost damage for crops, fruits, grapes, and even some tree species. In contrast, the thermal prerequisites for viticulture will be satisfied across the entire region, even at higher-elevation sites. These facets of regional climate change are made accessible to users and the public via an interactive field-resolving web portal. Altogether, they gravely challenge the historically developed land use systems in Lower Franconia and require timely adaptation and mitigation strategies.