Increased Weather Variability Research Articles

THERMODYNAMIC MODEL OF STUDYING THE DYNAMICS OF THE TEMPERATURE BALANCE BY CALCULATING HEAT ENERGY IN AGRICULTURAL SECTOR

This work is the result of the simulation of a thermodynamic model that investigates the dy- namics of the temperature balance due to the transfer of thermal energy. A proposed scheme outlines the rheological heat transfer characteristics of an object featuring an insulated surface, along with accompany- ing graphs illustrating irreversible rheological transformations. The primary equation governing heat ex- change, incorporating a chemical reaction, is presented, and the equation dictating the rate of heat energy transfer along the object's length is derived. The subsequent step involves advancing physical- mathematical models to depict the conversion of thermal energy into various states of the object. This ad- vancement aims to facilitate an evaluation of the overall temperature regimen of agricultural entities and optimize the heating procedures. In recent years, the agricultural sector has faced substantial challenges attributed to climate change. Climate change impacts on agriculture encompass elevated temperatures, increased weather variability, shifting agroecosystem boundaries, invasive species, pests, and frequent ex- treme weather events. These changes possess the potential to disrupt agricultural yields and food security, underscoring the importance of comprehending and managing temperature dynamics within agricultural systems. This research delves into the core of temperature regulation within agricultural objects, employing a thermodynamic model that not only considers heat exchange but also incorporates the influence of chemical reactions. Through the derivation of equations characterizing the speed of heat energy transfer and the development of physical-mathematical models for thermal energy transformation, this study offers a robust framework for evaluating and refining the temperature regime of agricultural objects. This re- search paves the way for further advancements in the comprehension and management of temperature dynamics within agricultural systems. As climate change persists in posing challenges to the sector, the knowledge and models developed here will serve as invaluable tools in optimizing heating procedures, en- hancing agricultural resilience, and securing global food production. In summary, this study significantly contributes to our understanding of temperature balance and heat energy transfer within agricultural ob- jects. It represents a crucial stride towards addressing the challenges posed by climate change in agricul- ture.The suggested thermodynamic model, along with its corresponding equations, lays a robust ground- work for forthcoming investigations and practical implementations. Ultimately, this development stands to enhance the agricultural sector and contribute to global food production.

Effects of changes in climatic means, variability, and agro-technologies on future wheat and maize yields at 10 sites across the globe

To address the rising global food demand in a changing climate, yield gaps (YG), the difference between potential yields under irrigated (YP) or rainfed conditions (YWL) and actual farmers’ yields (Ya), must be significantly narrowed whilst raising potential yields. Here, we examined the likely impacts of climate change (including changes in climatic variability) and improvements in agricultural technologies on crop yields and yield gaps. Eight rigorously tested crop simulation models were calibrated for wheat and maize and run at 10 different sites around the world. Simulations were performed to estimate YP, YWL and yields achievable under three locally defined technology packages: TP0 represents average farmer's practice, while TP1 and TP2 are increasingly advanced technologies. Simulations were run for the baseline (1981–2010) and twelve future climate scenarios for 2050, representing changes in the means of climate variables and in the variability of daily temperature and dry/wet spell durations. Our basic hypotheses were that (H1) mean climate changes combined with increased weather variability lead to more negative yield impacts than mean climate changes alone, and (H2) advanced technologies would serve as effective adaptations under future climatic conditions. We found that crop responses were dependent on site characteristics, climate scenarios and adopted technologies. Our findings did not support H1. As for H2, the improved technology packages increased wheat and maize yields at all sites, but yield gap reduction varied substantially among sites. Future studies should consider a broader range of climate scenarios and methods for analysing potential shifts in climate variability. Moreover, it is recommended to co-create and evaluate climate zone-specific climate-smart crop production technologies in interaction with a wide range of local stakeholders.

The Potential of Bison Restoration as an Ecological Approach to Future Tribal Food Sovereignty on the Northern Great Plains

Future climate projections of warming, drying, and increased weather variability indicate that conventional agricultural and production practices within the Northern Great Plains (NGP) will become less sustainable, both ecologically and economically. As a result, the livelihoods of people that rely on these lands will be adversely impacted. This is especially true for Native American communities, who were relegated to reservations where the land is often vast but marginal and non-tribal operators have an outsized role in food production. In addition, NGP lands are expected to warm and dry disproportionately relative to the rest of the United States. It is therefore critical to identify models of sustainable land management that can improve ecological function and socio-economic outcomes for NGP communities, all while increasing resilience to a rapidly changing climate. Efforts led by Native American Nations to restore North American Plains bison (Bison bison bison) to tribal lands can bring desired socio-ecological benefits to underserved communities while improving their capacity to influence the health of their lands, their people, and their livelihoods. Ecological sustainability will depend on the restoration of bison herds and bison’s ability to serve as ecosystem engineers of North America’s Plains. The historically broad distribution of bison suggests they can adapt to a variety of conditions, making them resilient to a wide range of management systems and climates. Here we review bison’s ecological, cultural, and economic value using four case studies from tribal communities within the NGP. We discuss the potential contributions of bison to food sovereignty, sustainable economies, and conservation of a working landscape with limited protections and significant risk of conversion. The ecological role of bison within this setting has potential due to cultural acceptance and the vast availability of suitable lands; however, it is critical to address tribal needs for funding support, enhanced community capacity, and solving complex landownership for these goals to be achieved.

ГРАЖДАНСКАЯ НАУКА КАК ИНСТРУМЕНТ ИНФОРМАЦИОННОГО ОБЕСПЕЧЕНИЯПРИНЯТИЯ РЕШЕНИЙ В РОССИЙСКОЙ АРКТИКЕ В УСЛОВИЯХ ИЗМЕНЕНИЯ КЛИМАТА

Rapid climate change in the Arctic requires management solutions that are based on timely and reliable factual data. In this context, the urgency ofthe problem of finding effective ways for obtaining such information is increasing. This article aims to substantiate the possibility of using citizen science as a new tool for information support of decision-making with respect to the socio-economic development of the Arctic Zone of the Russian Federation, and as a tool especially necessary when developing strategies for adaptation to climate change. Citizen science is a concept that implies increasing openness of science to society and the conduct of scientific research with the involvement of volunteers. The article provides an overview of the content of the concept of citizen science andthe principles and methods on which it is based.The article describes the results of an interdisciplinary study to identify the perceptions of inhabitants of the Murmansk region on climate change and the presumably associated with it changes in biodiversity in this region of the Russian Arctic. For the first time, based on the methods of citizen science, the data on theperceptions of inhabitants of the Murmansk region on climate and biodiversity changes in the region over a thirty-year period hasbeen obtained, and the comparisons of this information with the data from scientific observations were made. It was identified that inhabitants distinguish several trends in climate change in the region, consistent with the data of meteorological observations: climate warming, especially in the winter months; increased weather variability; increased duration of the off-season periods. Matching the observations of the respondents with biological scientific data made it possible to conclude that as a result of the combined influence of natural and anthropogenic factors (including climatic ones) new species of pests and fungi appeared in the region, and the number and proportion of valuable fish species within the basin of Lake Imandra have declined. It is shown that the subjective perceptionsof climate change should be taken into account in the management process, since this is oneof the key characteristics of the comfort of people living in the territory and a motive for actions, including adaptation.The article offers proposals on the inclusion of citizen scientists and citizen science data in the governing process through inter-sectoral commissions for the development of strategies for adaptation to climate change and other institutions of public participation.

Investigating Pre-service Science, Technology, and Mathematics Teachers’ Attitudes toward Climate Change in Nigeria

The study investigated attitudes toward climate change among 480 pre-service science, technology, and mathematics (STM) teachers from four higher institutions of learning in Southwest, Nigeria using the quantitative research method within the blueprint of the descriptive survey design. Data collected using climate change attitude survey were analysed using the descriptive statistics of percentages, mean, and standard deviation and inferential statistics of factor analysis and independent samples t-test. Findings revealed that attitudes toward climate change assessed by the climate change attitude survey was a multi-dimensional construct (perceived beliefs component and intentions component). Gender differences in attitudes toward climate change among pre-service STM teachers were not significant even at the subscale level of perceived beliefs and intentions. In addition, the pre-service STM teachers showed a moderate level of attitudes toward climate change. In conclusion, there is need for a concerted effort to protect the earth from increased weather variability and the Nigerian government at all levels has both international and domestic commitments to reduce greenhouse gas emissions to ensuring sustainable human development. Future studies in Nigeria and elsewhere should conduct a confirmatory factor analysis on the climate change attitude survey to further generalise the findings of this study.

Soil Water Holding Capacity Mitigates Downside Risk and Volatility in US Rainfed Maize: Time to Invest in Soil Organic Matter?

Yield stability is fundamental to global food security in the face of climate change, and better strategies are needed for buffering crop yields against increased weather variability. Regional- scale analyses of yield stability can support robust inferences about buffering strategies for widely-grown staple crops, but have not been accomplished. We present a novel analytical approach, synthesizing 2000–2014 data on weather and soil factors to quantify their impact on county-level maize yield stability in four US states that vary widely in these factors (Illinois, Michigan, Minnesota and Pennsylvania). Yield stability is quantified as both ‘downside risk’ (minimum yield potential, MYP) and ‘volatility’ (temporal yield variability). We show that excessive heat and drought decreased mean yields and yield stability, while higher precipitation increased stability. Soil water holding capacity strongly affected yield volatility in all four states, either directly (Minnesota and Pennsylvania) or indirectly, via its effects on MYP (Illinois and Michigan). We infer that factors contributing to soil water holding capacity can help buffer maize yields against variable weather. Given that soil water holding capacity responds (within limits) to agronomic management, our analysis highlights broadly relevant management strategies for buffering crop yields against climate variability, and informs region-specific strategies.

What would farmers do? Adaptation intentions under a Corn Belt climate change scenario

This paper examines farmer intentions to adapt to global climate change by analyzing responses to a climate change scenario presented in a survey given to large-scale farmers (n = 4778) across the US Corn Belt in 2012. Adaptive strategies are evaluated in the context of decision making and farmers’ intention to increase their use of three production practices promoted across the Corn Belt: no-till farming, cover crops, and tile drainage. This paper also provides a novel conceptual framework that bridges a typology of adaptation with concepts that help predict intentionality in behavior change models. This conceptual framework was developed to facilitate examination of adaptive decision making in the context of agriculture. This research effort examines key factors that influence farmers’ intentions to increase their use of the practices evaluated given a climate change scenario. Twenty-two covariates are examined across three models developed for no-till farming, cover crops, and tile drainage. Findings highlight that farmers who believed they should adjust their practices to protect their farm from the negative impacts of increased weather variability were more likely to indicate that they would increase their use of each of the practices in response to climate change. Additionally, visiting with other farmers to observe their practices was positively associated with farmers’ intentions to increase their use of the adaptive strategies examined. Farmers who were currently using no-till farming, cover crops, and tile drainage were also more likely to plan to increase their use of these practices in response to increased weather variability associated with climate change. However, farmers who reported high levels of confidence in their current practices were less likely to plan on changing their use of these practices in response to climatic changes.

The vulnerability of the US food system to climate change

The climate change vulnerability of a food system is a function of the exposure of the system to specific climate effects, the sensitivity of the system to those effects, and the capacity of the system adapt to those effects in order to maintain system integrity. A synthesis of recent literature conducted to explore the vulnerability of the US food system to climate change suggests that the interaction between regional climate change effects and the geographic specialization and concentration of agricultural production in the USA increases the vulnerability of the US food system to climate change. Vegetable and fruit production in the Pacific states are particularly sensitive to reduced water supplies, warmer winters, and more variable spring weather. Grain production in the Great Plains and the Midwest is sensitive to more variable weather, warmer winters, heat wave, and hot summer nights and flooding caused by more frequent heavy rains. The concentration of beef, pork, and poultry production in confined animal feeding operations located in the southern Great Plains and the Southeast is particularly sensitive to increased frequency and intensity of extreme weather and interruptions in feed, water, and power supplies associated with interactions between land, water, and energy use that amplify climate change effects. There is evidence that climate change is already causing disruptions throughout the US food system. Farmers and ranchers in the US report that increased weather variability and more frequent and intense weather extremes have increased the costs and complexity of food production. Businesses operating in the US agricultural supply, processing, distribution, and retailing sectors are actively managing supply networks to reduce disruptions associated with climate change effects. Food systems that rely on external or distant resources and specialized production, supply, and marketing chains appear to be particularly vulnerable to global environmental change. These characteristics, widely recognized as critical challenges to the sustainability of the US food system, take on new importance as barriers to climate resilience.

Optimization of Agricultural Field Workability Predictions for Improved Risk Management

Improved prediction of the days available for field work, or field working days (FWDs), is an important consideration for adapting farming systems to increased weather variability. We developed modeling approaches to estimate robust soil moisture thresholds for FWDs. We used simulated soil moisture to train the model on the same type of data that would be used for FWD forecasting (prediction). These new models were tested against previously suggested thresholds for field workability. Model 1 used historical field work and weather records from three crop research centers in a logistic regression model. A soil moisture threshold of 1.10 times the plastic limit (1.10PL) was identified. Model 2 identified statewide soil moisture and temperature thresholds by optimizing the root mean square error of the predicted number of weekly statewide FWDs across a 52‐yr data set. The resulting thresholds of either 0.88PL or 0.73FC (field capacity) and an average temperature requirement of at least 6°C yielded statistically smaller absolute errors for the state average FWDs and in eight of the nine crop reporting districts. The Model 2 thresholds also eliminated systematic overprediction present in previous thresholds. These results demonstrate that immutable theoretical thresholds for FWDs based on field‐measured soil moisture can be suboptimal for prediction at a larger spatial scale due to consistent bias.

No evidence of the effect of extreme weather events on annual occurrence of four groups of ectothermic species.

Weather extremes may have strong effects on biodiversity, as known from theoretical and modelling studies. Predicted negative effects of increased weather variation are found only for a few species, mostly plants and birds in empirical studies. Therefore, we investigated correlations between weather variability and patterns in occupancy, local colonisations and local extinctions (metapopulation metrics) across four groups of ectotherms: Odonata, Orthoptera, Lepidoptera, and Reptilia. We analysed data of 134 species on a 1×1 km-grid base, collected in the last 20 years from the Netherlands, combining standardised data and opportunistic data. We applied dynamic site-occupancy models and used the results as input for analyses of (i) trends in distribution patterns, (ii) the effect of temperature on colonisation and persistence probability, and (iii) the effect of years with extreme weather on all the three metapopulation metrics. All groups, except butterflies, showed more positive than negative trends in metapopulation metrics. We did not find evidence that the probability of colonisation or persistence increases with temperature nor that extreme weather events are reflected in higher extinction risks. We could not prove that weather extremes have visible and consistent negative effects on ectothermic species in temperate northern hemisphere. These findings do not confirm the general prediction that increased weather variability imperils biodiversity. We conclude that weather extremes might not be ecologically relevant for the majority of species. Populations might be buffered against weather variation (e.g. by habitat heterogeneity), or other factors might be masking the effects (e.g. availability and quality of habitat). Consequently, we postulate that weather extremes have less, or different, impact in real world metapopulations than theory and models suggest.

Rainfall Erosivity in Southeastern Nigeria

In developing land management plans to minimize erosion problem, it is imperative to provide quantitative information on aggressiveness of storms for identifying areas in the landscape which are sensitive to disturbances. The study established that rainfall erosivity (R) indices over Southeastern Nigeria range from very low to very high erosivity. Periods of very low erosivity coincided with the dry season months in the region while the very high R coincided with the rainy season peak periods (June-September). Calabar Owerri and Port-Harcourt recorded the highest erosive storms/ more months of very high erosivity index. The deterministic  relationship between kinetic energy of rains and erosivity pattern observed for the different stations showed that erosive rains contribute significantly to detachment of soil materials in the study area. The need for proper land use management and maintenance of surface vegetal covers cannot be overemphasized with increased weather variability. Monitoring of hydrologic regime and climate –related factors in the region as well as defining areas most vulnerable to erosion would help in erosion disaster management.Keywords: soil erosion, erosivity Index, land use management and rainfall

Integrating local and scientific weather knowledge as a strategy for adaptation to climate change in the Arctic

As the climate warms, stressors are developing that challenge the adaptive capabilities of Arctic peoples. In Nunavut, one of Canada’s Arctic territories, increased weather variability and changes in physical and climatic conditions are having profound effects on residents. One problem is that while these changes have magnified risks associated with travel and land-based activities, individuals lack sufficiently reliable and useful information on which to base decisions. In this paper, we argue that weather-related risk assessment can be improved by integrating local and scientific weather knowledge and making this information accessible to residents through the creation of weather hazards impact advisory groups. We present a qualitative case study of Iqaluit, the capital of Nunavut, using data from participant observation and semi-structured interviews conducted with indigenous and non-indigenous long-term residents in summer 2009. We examine how long-term residents of Iqaluit acquire, perceive, and use both local and scientific weather knowledge. We find that various barriers, such as a lack of land-based experience, cultural and linguistic differences, and an absence of social networks, prevent most people from obtaining all the information required to make fully informed decisions about the risks associated with land-based activities at different locations. Experienced hunters are perceived to be a reliable source of weather-related information, while scientific weather knowledge is not as accessible or informative as it could be. Increasing the potential use of traditional and scientific hazardous weather knowledge, by making both more universally accessible, can enhance strategies for adapting to climate change in the Arctic.

Using life-history traits to explain bird population responses to changing weather variability

Bird population dynamics are expected to change in response to increased weather variability, an expression of climate change. The extent to which species are sensitive to effects of weather on survival and reproduction depends on their life-history traits. We investigated how breeding bird species can be grouped, based on their life-history traits and according to weather-correlated population dynamics. We developed and applied the linear trait–environment method (LTE), which is a modified version of the fourth-corner method. Despite our focus on single traits, 2 strategies—combinations of several traits—stand out. As expected, breeding populations of waterfowl species are negatively impacted by severe winters directly preceding territory monitoring, probably because of increased adult mortality. Waterfowl species combine several traits: they often breed at ground or water level, feed on plant material, are precocial and are generally short-distance or partial migrants. Furthermore, we found a decline in population growth rates of insectivorous long-distance migrants due to mild winters and warm springs in the year before territory monitoring, which may be caused by reduced reproduction due to trophic mismatches. We identify species that are expected to show the most significant responses to changing weather variability, assuming that our conclusions are based on causal relationships and that the way species, weather variables and habitat interact will not alter. Species expected to respond positively can again be roughly categorized as waterfowl species, while insectivorous long-distance migrants are mostly expected to respond negatively. As species traits play an important role in constructing functional groups that are relevant to the provisioning of ecosystem services, our study enables the incorporation of ecosystem vulnerability to climate change into such functional approaches

Projected climate change causes loss and redistribution of genetic diversity in a model metapopulation of a medium‐good disperser

Climate change causes species ranges to shift geographically as individuals colonise new suitable temperature zones or fail to reproduce where climate conditions fall below tolerance levels. Little is known about the potential loss of genetic diversity in such dynamic ranges. We investigated the level and distribution of neutral genetic diversity in shifting metapopulations during three scenarios of temperature increase projected for this century and at various degrees of weather variability. We used an individual‐based and spatially explicit metapopulation model in which temperature zones were simulated to move across a fragmented landscape following different climate change scenarios. Although the connectivity between habitat patches allowed the species, modelled after the middle spotted woodpecker Dendrocopos medius, to move along with the shifting temperature range, existing neutral genetic diversity was lost under all three temperature increase scenarios. This was independent of the loss of individuals. The explanation for this effect is that only a part of the original genetic variation moved into the newly colonised habitat. Under increased weather variability the number of individuals and the number of alleles per locus were persistently lower. However, the pattern of changes in allele distributions under temperature zone shifts was the same under all weather variability levels. Genetic differentiation between populations had a tendency to increase at metapopulation range margins, but decreased again when population sizes increased in time. Increased weather variability led to increased variation around the mean genetic differentiation across the metapopulation. Our results illustrate the usefulness of more realistic models for studying the effects of climate change on metapopulations. They indicate that biodiversity monitoring indices based on species occurrence and abundance are not a good proxy for the trend in the level of genetic diversity. Further, the results underline the importance of conserving areas where species have existed for a long time as modern refugia for genetic diversity.

A GEOGRAPHIC ANALYSIS OF GRAIN CORN YIELD TRENDS IN ONTARIO USING A COMPUTERIZED LAND INFORMATION BASE

The geographic variability of grain corn yield trends in Ontario for the period 1961–1982, and the relative importance of nitrogen fertilizer, weather variability, technology and cropland expansion on these trends was investigated. Of particular interest was the difference in yield response among regions to the increased weather variability in the 1970s. After the effects of weather on yield were removed, linear and nonlinear as well as positive and negative technology (time) trends were observed, depending on the suitability of soils and climate for corn in each area. Yield increases resulting from technology improvements (assuming normal weather) averaged 2, 1 and 0.3% per year in the most suitable, intermediate and marginal areas, respectively. Grain corn yields were more closely related to weather variability than to nitrogen fertilizer sales or cropland expansion. Although N fertilizer increased coincidentally with yield in the 1960s, a low correlation (r = 0.16) over the whole 1965–1982 period indicated the likely importance of other factors on yield. Weather parameters related to temperature and precipitation explained 21–64% of the variation in yield in multiple linear regression analyses. Including time parameters (technology) in the regression improved the explained variance for most map units (R2 = 0.36–0.79). A decrease in yields and an increase in yield fluctuations observed in many areas in the mid-1970s appeared to be related to increased weather variability, the greatest effect of which was in the areas least suited to corn. Grain corn yields have continued to increase in some areas of Ontario while in other areas yields have plateaued or decreased marginally. This pattern is distributed geographically north and eastward from the most suited regions. Key words: Corn yield, weather variability, nitrogen fertilizer, cropland expansion, land information, data bases