The mean difference for good governance between organic and conventional farming systems was significantly different for sub-themes, mission statement and full-cost accounting.For instance, ‘Mission statement’ was significantly better for organic as organic farmers were aware of their cooperative certification and what it stood for.Similarly, in Ssebunya et al., the governance dimension recorded low scores.The sustainability performance of farming systems has several important implications for cocoa farm managers/farmers.The context in which farmers manage their cocoa farms has changed rapidly, often with little warning.The environmental specifications for producing cocoa, the socially stringent measures of abolition of child labour ensure fairness in labour conditions.These create uncertainty regarding future threats and potentials of producing cocoa through the organic or conventional farming system.This article emphasises the need to think about sustainability at the farm level at a basic level rather than the crop level.This underscores the need for improvement across the value chain.Notably, the paper highlights that farm level activities are within broader social and natural boundaries.An accurate picture of the sustainability performance of a farming system cannot be developed if these boundaries are ignored.Explicit recognition of these points in managerial decision-making would represent a marked departure for crop level that have thus far been reluctant to look beyond their walls.The SMART-FARM Tool provides the needed basis for measuring the economic, environmental, good governance and social impacts of farming systems.This, in turn, would help decision-makers better understand their sustainability risks and opportunities.This is needed because farming systems must be proactive in addressing any potential economic, environmental,vertical grow table good governance and social challenges that could emerge throughout their value chains.
Given the significant number and variety of these sustainability challenges, farming systems must prioritise the issues that need the most urgent attention.The sustainability performance of farming systems using the SMART-FARM tool provides a basis for developing comprehensive strategies to improve performance and informed decision making towards prioritising farm outputs.Implementing these strategies comes at a cost so that farmers need to tackle the inevitable tradeoffs between efficiency and adaptability.However, unless farmers master this challenge, they cannot ensure the sustainability of their farms.Climate change-induced weather anomalies, such as extreme droughts and intense rainfalls, have been increasingly observed in places where people are highly vulnerable to their various effects in recent years.Assessing the vulnerability and unequal coping capabilities to climate change and weather events has been a focus of research attention, for example, vulnerability to flooding , urban vulnerability to extreme heat , agricultural vulnerability to drought , to climate change , and to severe snowstorms.It is observed that climate change has caused polar cold air and anomalously cold extremes moving southward as a result of winter atmospheric circulation at high northern latitudes associated with Arctic sea ice loss.The increases in winter storm intensity and frequency are evident in the US, especially in both mid- and high-latitude zones , and have produced non-negligible winter weather-related losses.However, as one of the commonly seen catastrophic weather events, winter storms and their impacts are often overlooked and understudied.Winter storms have been recognized as one of the catastrophic events leading to agricultural damage and loss.In farming regions, severe winter storms such as blizzards, unending snowfalls and extremely low temperatures can lead to building damage, animal losses, and reduction in milk production.Winter storms on farmlands can also create other issues including the removal of fertile soils, traditional routines failure, and crops being wiped out.In the US, the Midwest is well recognized as a major producer of vegetables, dairy, beef cattle, and pigs.It is also a region that has experienced severe cold-air outbreaks and record numbers of snowstorms.
However, research is notably lacking in the vulnerability of farm communities to increasing winter storm events.The Intergovernmental Panel on Climate Change has contributed to assessments on climate change impacts, adaptation, and vulnerability since 1990 and created the distinct definition of vulnerability in 1997.Many climate-related vulnerability studies adopted the IPCC’s definition of vulnerability as a function of exposure, sensitivity, and adaptive capacity.The three vulnerability dimensions are defined as 1) exposure that characterizes the stressors and the entities under stress, 2) sensitivity that characterizes the direct effects of the stresses, and 3) capacity of the system to cope, adapt or recover from the effects of those conditions.Building on the concept of vulnerability, several investigators have advanced the characterization of the vulnerability components and approaches to assessing vulnerability.Among them, Hahn et al.constructed the Livelihood Vulnerability Index and categorized major indicators into contributing dimensions of vulnerability to evaluate livelihood risks specifically resulting from climate change.Since then, the vulnerability index further evolved with the replacement and addition of other indicators to suit local contexts and to be more relevant for target groups.There has been an increasing recognition of the linkage between vulnerability and five core categories of capitals including natural, physical, human, social, and financial capital.These capitals were described in the Sustainable Livelihoods Framework as resources used in the vulnerable context to cope with short- and long-term problems and have been integrated into indices to measure adaptive capacity.Despite various indices developed to estimate the level of vulnerability of agricultural communities to extreme weather events, suitable metrics of rural winter storm vulnerability remain under explored.To address the lack of vulnerability assessment regarding threats of winter storms in agricultural regions, this study identified rural areas of different vulnerabilities and explained factors leading to these differences by integrating local knowledge, existing indices, and statistical analyses.The synthetic vulnerability index developed in this study was anticipated to serve as a tool for adaptation planning and be adjusted to suit other climate-related vulnerability assessments or study regions.It is located in the Midwest of the United States between 40◦35′ N-43◦ 30′ N latitude and 90◦ 8′ W- 96◦ 38′ W longitude.
The state comprises 35.7 million acres, with over 85 percent of the land farmed, and has long led nationally in hog, egg, corn, and soybean productions.Iowa has an estimated population of 3.17 million in 2020 and maintains a diversified economy dominated by agriculture, manufacturing, biotechnology, finance and insurance services, and government services.There are 21 out of a total of 99 counties designated as metropolitan statistical areas in Iowa.Main metropolitan cities with a population of more than 100,000 include the capital city of Des Moines in Polk County, Cedar Rapids in Linn County, and Davenport in Scott County.Iowa is located in the heart of the blizzard belt and experiences frigid temperatures as well as dramatic storms in the winter.Average winter temperatures in the state could drop well below freezing, for example, even as low as below 6 ◦F in Cedar Falls-Waterloo, Black Hawk County.Most field investigations in this study were conducted in Black Hawk County, where about 133, 000 people reside in its twin cities of Cedar Falls and Waterloo.The vulnerability was analyzed at the county level for which the complete data was available.This study conducted several semi-structured interviews in the counties of Black Hawk, Buchanan, Kossuth, and Washington to obtain farmers’ narrated perceptions on winter storm impacts.This step is important because the interviews with stakeholders can provide the necessary information and knowledge in the local context.During January to February 2019, 14 farmers that produced different types of commodities were selected using a purposive snowball sampling approach so that they can represent main on-farm activities such as crop farming and cattle ranching coded in the North American Industry Classification System.Among the interviewed farmers, 5 operated diversified farms producing animal and crop commodities, 3 operated crop farms, 4 operated livestock farms, 1 was an orchard farmer, and 1 was a poultry farmer.Their farms ranged in size from 0.25 acres for a chicken farm to 500 acres for a livestock farm.Each interview took between 30 min to 1 h to complete the questions covering topics of the three key components of vulnerability assessment.A detailed list of questions is provided in Appendix A.While the visited places did not cover the entire state, they spread across different parts of Iowa, collectively enabling a comprehensive view of winter-related issues on farms in the state.Table 2 summarizes the winter storm-related impacts on farms and Fig.2 presents the frequency of content mentioned by respondents.They have revealed that, mobile vertical grow tables in the face of winter storms, Iowa farmers were mostly concerned about animal health, building damage, water and feed shortage, and power outage.
Efficient information delivery, insurance, and windbreaks were considered important in reducing storm losses.Additionally, blizzard, extreme cold, strong wind, and icing appear to be among the main threats associated with winter storms.Extreme weather can cause significant losses and damages such as decreasing yields and commodity quality levels in agricultural production systems.The interview results showed that farmers were exposed to losses from extreme winter weather such as winter temperature fluctuations and ice storms that threaten animal health and power supplies.The increases in storm occurrences and temperature variation lead to higher exposure.Event occurrences and temperature deviation have been used in previous climatic vulnerability assessments to represent the frequency of exposure and the level of changes in daily mean weather conditions.In this study, winter storm occurrences and winter temperature deviation were selected to measure the different exposure of Iowa counties to winter.The data on event counts was collected from the Storm Event Database provided by the National Centers for Environmental Information , which contains records on the occurrence of threatening weather phenomena.Various winter-related event types were considered in this study, including blizzard, cold/wind chill, extreme cold/wind chill, frost/freeze, heavy snow, ice storm, strong wind, winter storm, and winter weather.A Python script was created to calculate the total event counts for all counties in Iowa during the winter months of December, January, and February between 2010 and 2017.Winter temperature deviation was calculated using the minimum and maximum temperatures for each county downloaded from Parameter-elevation Regressions on Independent Slopes Model website which provides climate observations in the US at multiple spatial/temporal resolutions.From the interview results, it was found that the immediate impacts of winter storms came from affected on-farm structures and activities such as animal husbandry and building damage.Poorly constructed buildings appear to increase sensitivity to climate impacts.Animal health can be threatened by low temperatures and restrained freshwater access.Livestock farms are highly dependent on the climate conditions of a given year and they have to make considerable efforts to prepare supplies, implement actions, and recover in the face of winter storms.On the contrary, crop farms appear less sensitive during winter since crops are usually harvested back in the autumn.Thus, animal commodities sale and building age were selected as sensitivity determinants and represented using the 2012 farm sale statistics retrieved from the United States Department of Agriculture QuickStats and the 2012–2016 housing characteristics data collected from the US Census Bureau.Adaptive capacity is the ability to take actions and make adjustments to reduce adverse impacts resulting from climate-related hazards.The ability to cope with extreme weather events varies depending on assets, tangible and intangible, that support people’s livelihoods.These livelihood resources are seen as “capitals” and can influence adaptive capacity and thus vulnerability.Based on the five forms of capitals described in the Sustainable Livelihoods Framework, this study identified multiple adaptive capacity indicators from five dimensions: Natural capital.Farms surrounded by trees as windbreaks are assumed to be more protected from strong wind, therefore less vulnerable.This study used a georeferenced, raster-formatted and cropland specific land cover data layer downloaded from CropScape to extract pasture and tree cover in each county.Pastures with windbreaks were identified using a specified search radius of 200 feet as the recommended distance of a proper tree windbreak.Financial capital.Poverty has been included as a vulnerability factor.It is assumed that households with lower income possess fewer assets such as equipment and appliances that can help with the maintenance of buildings and animals.Thus, farm income and poverty were included as indicators for financial capital.The poverty rate and farm income for the year of 2012 were collected from the US Census Bureau and USDA QuickStats, respectively.Physical capital.Access to the Internet is considered the dominant way to collect all sorts of environmental knowledge to assist with decision-making.With sufficient Internet access, households can stay informed and are more likely to benefit from new policies and plans launched in real-time.This mirrors the qualitative interview results that have highlighted the importance of information.In this study, internet access was indicated by internet operations collected from USDA QuickStats.